Please note that our Terms & Conditions and Privacy Notice are applicable.
On Promotion in Online & Essential Services
Some search tips we've found useful:
- Check the spelling of your search terms
- Use fewer or more general search terms
- Try browsing a category related to your search terms
Ads in other locations
4
Realistic 3d Renders for architecture and interior design firms. If interested please contact. See some of the works I did below
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 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 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;
If you need to self-tutor STATA, you can get a
STATA version 15-30-day trial
3y