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1
9d
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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
15d
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
17d
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
18d
1
18d
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/
22d
1
24d
2
R 600
NEGOTIABLE
SavedSave
12-inch 5 speed bicycle with bike stand. In good condition.
1mo
1
R 500
NEGOTIABLE
SavedSave
10-inch bicycle with 'fairy" wheels. Bike stand. In good condition.
1mo
2
R 450
NEGOTIABLE
SavedSave
Steel trunk. Can be locked. Size 900mm x 530mm x 410mm deep.
1mo
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
2mo
Certificated Natural Scientist. Statistical Science. The South African Council for Natural Scientific Professions. Registration No. 129447
https://www.sacnasp.org.za/scientists?q=&province=&field_id=&page=342
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
2mo
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
2mo
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/
2mo
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
2mo
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
2mo
1
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/10413/88221. 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 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 trialWhattsapp 0732177216
2mo
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
3mo
3
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
6mo
2
SavedSave
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
6mo
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