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Are yu looking for a helper we can assist you
5d
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Struggling with your CV? Join our online CV tutoring sessions or book a consultation and learn how to create a job-winning CV that gets you noticed by employers.
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STADIO B.Ed (IP) 1st-year exam notes & summaries (e-copies) covering ACL101, TLS101, AFA100, EHL100, NSTI101 & NSTI102.
Personal, self-made notes compiled from multiple textbooks and aligned with the module curriculum.
Each module includes detailed exam notes, simplified summaries, and quick revision notes
R50 per module.
WhatsApp: 072 970 2252
2mo
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If you're having any trouble with theory or map work, I can help.
Seasoned, retired Geog teacher with years of matric marking experience at your service!
1y
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;
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