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Chris Manyamba
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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
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 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
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;
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
2y
I AM A RESEARCHER, PHD in Agricultural Economics and assist students in their assignments on the following: Business Research, Economics, Entrepreneurship, Innovation, Operations and Supply Chain Management, Strategic Human Resource Management, Strategic Financial Management, Strategic Management
Strategic Marketing Management. I also assist with dissertation (proposal writing, data collection process, analysis and write up. Analysis using SPSS and STATA for quantitative and Atals ti for qualitative data.
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 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
For your chapter 4 thesis or research paper. Experienced STATISTICIAN/RESEARCHER and PHD Finalist with 10 plus years’ experience in quantitative analysis. Longitudinal and cross section data analysis methodologies. I have vast experience in large household surveys around SADC countries, have analysed and presented for the African Union as a PhD and independent consultant. For thesis, analysis and interpretation, I also coach through the analysis and interpretation (for ownership). In my part time I am provide the following expertise;
i. Univariate analysis: Frequencies (prevalence’s-epi studies), tables and graphs
ii. Bivariate analysis-correlations (pairwise, tetrachloric, correlograms-in time series);
ii. Multivariate-Regression analyses which cover ordinal, count, categorical and binary outcomes. Ordinary Least Squares, Partial/Pooled effects; Factor/Principal component analysis;
iii. Hypothesis testing -parametric tests e.g. paired t-tests, and non-parametric tests (e.g. Wilcoxon sign rank)
iv. For Likert scale data-normality tests (Wilk Shapiro tests, skewness, kurtosis)
iv. Pathway Analysis and Structural Equation Modelling (SEM), and its post estimation results
v. Time series: Autoregressive Conditional Heteroscedastic (ARCH) and Auto Regressive Distributed Lag (ARDL) family models. Stepwise analysis which includes settimg data to time series, white noise detection (stationarity tests), Dick Fuller or PPeroni unit root tests (VAR), Vector error correction models (VEC), Granger causality tests.
v. 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 regression, interactions (log rank, and Kaplan Meier survival functions graphs).
vi. Checking multicollenearity/endogeneity-Variance Inflation Factor (VIF in STATA), or any pre model estimation. Software experience: Excel, SPSS, STATA (advanced/excellent), EPI Info (intermediate), R (intermediate), SAS (Intermediate). Turnaround time: In a space of 5 days.
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/
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
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
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;
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
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
3y
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
2y
Certificated Natural Scientist. Statistical Sciences.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
2y
I am a PhD finalist at University of Pretoria and have vast experience in research and in individual subjects assignment assistance to students. Been a Tutor, assistant lecturer, marker, and thesis supervisor.1. THESIS/DISSERTATION- Proposal writing (Chapter 1-3)-Thesis/Dissertation Writing (Chapter 4-analysis and Chapter 5-discussion)-Editing, plagiarism2. ASSIGNMENT ASSISTANCE (space of 3 days)MASTER OF BUSINESS ADMINISTRATIONBusiness Research Economics Emotional and Spiritual Intelligence Entrepreneurship Innovation Operations and Supply Chain Management Strategic Human Resource Management Strategic Financial Management Strategic Management Strategic Marketing ManagementPOSTGRADUATE DIPLOMA IN BUSINESS MANAGEMENT (PDBM)Advanced Project Management Advanced Human Resource Management Financial Management and Management Accounting Organisational Strategy, Planning and Management Fundamentals of Business ResearchDOCTORATE OF BUSINESS MANAGEMENT (DBM)Research at a Doctoral Level3. PORTFOLIO OF EVIDENCE (POE)Assistance with Formative AssessmentsTurnaround time: average is 3 daysWhatsApp: 073 217 7216
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