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For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis.
See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-index
My Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/
Also see https://researchspace.ukzn.ac.za/handle/10413/8822
I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.
Overall I provide the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
1y
Certificated Natural Scientist. Statistical Science
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling; 2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs; 3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data; 4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis); 5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis); 6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis; 7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results 8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests; 9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs); 10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation; 11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
1y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
1y
For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis.See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexMy Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/Also see https://researchspace.ukzn.ac.za/handle/10413/8822I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.Overall I provide the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trialWhatsApp 0732177216
2y
For your chapter 4/5 thesis or research paper. Experienced
STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in
quantitative analysis. I am providing the following quantitative analysis and
modelling expertise;
1.
Proposal development
including study design and sampling;
2.
Univariate analysis: Frequencies. Means and
std deviations for continuous data, tables and graphs;
3.
Bivariate analysis:
pairwise correlation, Spearman’s for non-parametric and Pearson’s for
normally distributed data;
4.
For Likert scale data, reliability (Cronbach’s alpha) and
normality tests (Wilk Shapiro
tests, skewness, kurtosis);
5.
Hypothesis testing
-parametric tests e.g. paired t-tests, and non-parametric tests (e.g.
Wilcoxon sign rank, Kruskal Wallis);
6.
Multivariate-Regression analyses which cover
ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS),
Partial/Pooled effects; Factor/Principal component analysis;
7.
Pathway
Analysis and Structural
Equation Modelling (SEM), and its
post estimation results
8.
Time-series,
Econometric Models: Autoregressive
Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL)
family models. The stepwise analysis includes setting data to time series,
white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root
tests (VAR), Vector error correction models (VEC), Granger causality tests;
9.
Survival analysis (epidemiological): Includes
setting data to survival, run descriptive stats with survival analysis family
of analysis. Survival analysis: Censoring, prevalence and incident rates,
regression models e.g. Cox proportionate regression, interactions (log-rank,
and Kaplan Meier survival functions graphs);
10.
Checking multicollinearity/endogeneity-Variance
Inflation Factor (VIF in STATA), or any pre-model estimation;
11.
Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate).
Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a
STATA version 15-30-day trial
2y
For your chapter 4/5 thesis or research paper. Experienced
STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in
quantitative analysis. I am providing the following quantitative analysis and
modelling expertise;
1.
Proposal development
including study design and sampling;
2.
Univariate analysis: Frequencies. Means and
std deviations for continuous data, tables and graphs;
3.
Bivariate analysis:
pairwise correlation, Spearman’s for non-parametric and Pearson’s for
normally distributed data;
4.
For Likert scale data, reliability (Cronbach’s alpha) and
normality tests (Wilk Shapiro
tests, skewness, kurtosis);
5.
Hypothesis testing
-parametric tests e.g. paired t-tests, and non-parametric tests (e.g.
Wilcoxon sign rank, Kruskal Wallis);
6.
Multivariate-Regression analyses which cover
ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS),
Partial/Pooled effects; Factor/Principal component analysis;
7.
Pathway
Analysis and Structural
Equation Modelling (SEM), and its
post estimation results
8.
Time-series,
Econometric Models: Autoregressive
Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL)
family models. The stepwise analysis includes setting data to time series,
white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root
tests (VAR), Vector error correction models (VEC), Granger causality tests;
9.
Survival analysis (epidemiological): Includes
setting data to survival, run descriptive stats with survival analysis family
of analysis. Survival analysis: Censoring, prevalence and incident rates,
regression models e.g. Cox proportionate regression, interactions (log-rank,
and Kaplan Meier survival functions graphs);
10.
Checking multicollinearity/endogeneity-Variance
Inflation Factor (VIF in STATA), or any pre-model estimation;
11.
Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate).
Turnaround time for analysis, interpretation and write up: In a space of 5 days;
12.
If you need to self-tutor STATA, you can get a
STATA version 15-30-day trial on https://www.stata.com/customer-service/evaluate-stata/. 072 3548043
3y
For your chapter 4/5 thesis or research paper. Experienced
STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in
quantitative analysis. I am providing the following quantitative analysis and
modelling expertise;
1.
Proposal development
including study design and sampling;
2.
Univariate analysis: Frequencies. Means and
std deviations for continuous data, tables and graphs;
3.
Bivariate analysis:
pairwise correlation, Spearman’s for non-parametric and Pearson’s for
normally distributed data;
4.
For Likert scale data, reliability (Cronbach’s alpha) and
normality tests (Wilk Shapiro
tests, skewness, kurtosis);
5.
Hypothesis testing
-parametric tests e.g. paired t-tests, and non-parametric tests (e.g.
Wilcoxon sign rank, Kruskal Wallis);
6.
Multivariate-Regression analyses which cover
ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS),
Partial/Pooled effects; Factor/Principal component analysis;
7.
Pathway
Analysis and Structural
Equation Modelling (SEM), and its
post estimation results
8.
Time-series,
Econometric Models: Autoregressive
Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL)
family models. The stepwise analysis includes setting data to time series,
white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root
tests (VAR), Vector error correction models (VEC), Granger causality tests;
9.
Survival analysis (epidemiological): Includes
setting data to survival, run descriptive stats with survival analysis family
of analysis. Survival analysis: Censoring, prevalence and incident rates,
regression models e.g. Cox proportionate regression, interactions (log-rank,
and Kaplan Meier survival functions graphs);
10.
Checking multicollinearity/endogeneity-Variance
Inflation Factor (VIF in STATA), or any pre-model estimation;
11.
Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate).
Turnaround time for analysis, interpretation and write up: In a space of 5 days;
12.
If you need to self-tutor STATA, you can get a
STATA version 15-30-day trial on https://www.stata.com/customer-service/evaluate-stata/ 072 3548043
3y
Certificated Natural Scientist. Statistical ScienceFor your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
2y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
3y
Certificated Natural Scientist. Statistical Sciences.For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis.See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexMy Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/Also see https://researchspace.ukzn.ac.za/handle/10413/8822Whattsapp 0732177216I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.Overall I provide the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
2y
For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis.See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexMy Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/Also see https://researchspace.ukzn.ac.za/handle/10413/8822I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.Overall I provide the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
4y
For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexMy Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.Overall I provide the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Software experience: Excel, SPSS, STATA, R, EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
4y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexa. I analyse, interpret and write up Chapter 4, which you then discuss in Ch5.Overall I provide the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Software experience: Excel, SPSS, STATA, R, EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
4y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;1. Proposal development including study design and sampling;2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
4y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;
12. If you need to self-tutor STATA, you can get a STATA version 15-30-day trial. 072 3548043
2y
For your chapter 4 and 5 thesis chapter. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis.
See https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-index
My Linkdin profile: https://www.linkedin.com/in/christopher-manyamba-04490713/
Also see https://researchspace.ukzn.ac.za/handle/10413/8822
I analyse, interpret and write up Chapter 4 (15-25 pages, or more), which you then discuss in Ch5.
Overall I provide the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
0723548043
2y
For your chapter 4/5 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in quantitative analysis. I am providing the following quantitative analysis and modelling expertise;
1. Proposal development including study design and sampling;
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
2y
In my part time I analyse, interpret and write up chapter 4/5 thesis, in 3-5 days. I am an experienced STATISTICIAN/RESEARCHER and PHD Finalist (University of Pretoria), with 15 plus years’ experience in quantitative analysis. My experience is specifically on cross sectional and longitudinal research (econometric models and survival models) processes. I have also supervised Masters thesis. My profiles online for more
https://www.linkedin.com/in/christopher-manyamba-04490713/
http://oasis.col.org/handle/11599/3934?show=full
https://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-index
https://researchspace.ukzn.ac.za/handle/10413/8822
1. Proposal development: Intro, Literature review, Methodology (study design, approach, sampling, reliability, ethical issues)
2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;
3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;
4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);
5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);
6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;
7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;
9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);
10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;
11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). If you need to self-tutor STATA, you can get a STATA version 15-30-day trial
Whattsapp 0732177216
2y
For your chapter 4/5 thesis or research paper. Experienced
STATISTICIAN/RESEARCHER and PHD Finalist with 15 plus years’ experience in
quantitative analysis. I am providing the following quantitative analysis and
modelling expertise;
1.
Proposal development
including study design and sampling;
2.
Univariate analysis: Frequencies. Means and
std deviations for continuous data, tables and graphs;
3.
Bivariate analysis:
pairwise correlation, Spearman’s for non-parametric and Pearson’s for
normally distributed data;
4.
For Likert scale data, reliability (Cronbach’s alpha) and
normality tests (Wilk Shapiro
tests, skewness, kurtosis);
5.
Hypothesis testing
-parametric tests e.g. paired t-tests, and non-parametric tests (e.g.
Wilcoxon sign rank, Kruskal Wallis);
6.
Multivariate-Regression analyses which cover
ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS),
Partial/Pooled effects; Factor/Principal component analysis;
7.
Pathway
Analysis and Structural
Equation Modelling (SEM), and its
post estimation results
8.
Time-series,
Econometric Models: Autoregressive
Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL)
family models. The stepwise analysis includes setting data to time series,
white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root
tests (VAR), Vector error correction models (VEC), Granger causality tests;
9.
Survival analysis (epidemiological): Includes
setting data to survival, run descriptive stats with survival analysis family
of analysis. Survival analysis: Censoring, prevalence and incident rates,
regression models e.g. Cox proportionate regression, interactions (log-rank,
and Kaplan Meier survival functions graphs);
10.
Checking multicollinearity/endogeneity-Variance
Inflation Factor (VIF in STATA), or any pre-model estimation;
11.
Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate).
Turnaround time for analysis, interpretation and write up: In a space of 5 days;
If you need to self-tutor STATA, you can get a
STATA version 15-30-day trial
2y
Certificated
Natural Scientist. Statistical Science. The South African Council for Natural Scientific Professions Registration No. 129447https://www.sacnasp.org.za/scientists?q=&province=&field_id=&page=342In my part time I analyse, interpret and write up chapter 4/5 thesis, in 3-5 days. I am an experienced STATISTICIAN/RESEARCHER and PHD Finalist (University of Pretoria), with 15 plus years’ experience in quantitative analysis. My experience is specifically on cross sectional and longitudinal research (econometric models and survival models) processes. I have also supervised Masters thesis. My profiles online for morehttps://www.linkedin.com/in/christopher-manyamba-04490713/http://oasis.col.org/handle/11599/3934?show=fullhttps://www.up.ac.za/news/post_1722144-up-student-wins-fellowship-to-study-womens-empowerment-indexhttps://researchspace.ukzn.ac.za/handle/10413/88221. Proposal development: Intro, Literature review, Methodology (study design, approach, sampling, reliability, ethical issues)2. Univariate analysis: Frequencies. Means and std deviations for continuous data, tables and graphs;3. Bivariate analysis: pairwise correlation, Spearman’s for non-parametric and Pearson’s for normally distributed data;4. For Likert scale data, reliability (Cronbach’s alpha) and normality tests (Wilk Shapiro tests, skewness, kurtosis);5. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank, Kruskal Wallis);6. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares (OLS), Partial/Pooled effects; Factor/Principal component analysis;7. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results8. Time-series, Econometric Models: Autoregressive Conditional Heteroscedastic (ARCH) and Auto-Regressive Distributed Lag (ARDL) family models. The stepwise analysis includes setting data to time series, white noise detection (stationarity tests), Dick Fuller or P-Peroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests;9. Survival analysis (epidemiological): Includes setting data to survival, run descriptive stats with survival analysis family of analysis. Survival analysis: Censoring, prevalence and incident rates, regression models e.g. Cox proportionate regression, interactions (log-rank, and Kaplan Meier survival functions graphs);10. Checking multicollinearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre-model estimation;11. Software experience: Excel, SPSS, STATA EViews (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). If you need to self-tutor STATA, you can get a STATA version 15-30-day trialWhattsapp 0732177216
2y
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