New approaches in statistical analysis

Statistics is old fashion, now data science is the new flavor demanded discipline.

​

What is statistical learning?

​

Kuwaiti market and data science.

​

​

Descriping data

Measures of central tendency

Mean, Median, Mode, mid-range, ..., etc.

​

Measures of Variations

Standard Deviation, Range, Quartile, ..., etc

​

Detecting for any possible outliers

Using z-scores, Box-plot, Residuals Analysis, Studentized t-test, ..., etc.

​

Test for Normality of the data

Shapiro test, Kolomogrove test, Histogram, Q-Q-plot, ..., etc.

Test of hypothesis

To test weather there is any significant differences between the groups levels.

for Parametric:

t-test / paired t test, ANOVA, Chi-square

for non-Parametric:

Mann–Whitney U test / Wilcoxon rank-sum test, Kruskal-Wallis H test, Fisher test.

Correlation and Regression

The data for this workshop id about survey respondents from Kuwait population who expressing their feeling about the impact of online training in their performance.

Results Satistical Interpretation

The best way to interpret your statistical results tables and figures in to see how the scholars in your fields went through the statistical interpretation. But, in this slide, I will provide some helpful techniques to generate the statistical interpretation using the recommendation deep learning system