daksh-intwala / hypothesis-testing---student-s-t-test-anova-test

Hypothesis Testing is done on a payroll database using various testing methods.

Hypothesis-Testing---Student-s-t-test-ANOVA-test

Hypothesis Testing is done on a payroll database using various testing methods.

Dataset link: https://drive.google.com/file/d/1ZyB6LInrRhh27Knp6CnPcolE5muIDWo2/view?usp=sharing

1. Importing Relevant Librari es: Pandas, Numpy, Seaborn, Matplotlib, Sklearn, Scipy, Warning, Researchpy

2. Exploratory Data Analysis:

• Checking variables df.info()
• Checking Null Values df.isnull().sum()
• Correlation Matrix
• Visualization

3. Preparing the dataset:

• Dropping Correlated Rows
• Removing Dollar Sign & Converting to float
• Renaming the fields
• Scaling the fields
• Grouping the dataset

4. Normality Test:

• Visually: Q-Q Plot
• Shapiro-Wilk Test

5. Sampling: Divided into 4 samples according to year 2013,2014,2015,2016

6. Levene’s test: Checking variance

Stats, Pvalue = stats.levene(sample_1['Annual_sal'], sample_2['Annual_sal'])

7. Student’s test:

std_err = np.std(sample_3['Base_Pay'])/np.sqrt(48063) z_stat = (np.mean(sample_4['Base_Pay'])-np.mean(sample_3['Base_Pay']))/std_err

8. Student’s Independent test:

t_stat, df, cv, p = independent_ttest(data1, data2, alpha)

9. ANOVA test:

_,p=st.f_oneway(groups[comb[0]],groups[comb[1]])