Course Content

Introduction to Statistics For Data Analysis and Data Science

5m 22s

How to use LearnVern

3m 20s

Fundamentals of Statistics

15m 45s

Basics of Descriptive Statistics

12m 47s

Measures of Frequency

10m 47s

Measures of Central Tendency - Mean

9m 9s

Measures of Central Tendency - Median

4m 48s

Measures of Central Tendency - Mode

5m 21s

Measures of Variability - Mean Absolute Deviation

7m 33s

Measures of Variability - Variance

7m 42s

Measures of Variability - Standard Deviation

10m 36s

Measures of Position

16m

Measures of Shape - Skewness

10m 36s

Measures of Shape - Kurtosis, Box and Whisker Plot

8m 51s

Assignment : Descriptive Statistics

3m 54s

Quiz : Descriptive Statistics

12m

Hypothesis Testing in Data Science

7m 27s

Null and Alternative Hypothesis

9m 6s

Making a Decision - Reject or Fail to Reject Null Hypothesis

9m 21s

Type I & Type II Errors

12m 47s

Covariance and Correlation Coefficients

11m 47s

Types of Correlation Coefficients

15m 49s

Assignment : Hypothesis Testing

3m 53s

Quiz : Hypothesis Testing

5m

Types of Statistical Tests

3m 9s

Z-Test: Critical Value Method

13m 9s

Examples of Z-Test: Critical Value Method

9m 20s

Z-Test: P-Value Method

9m 33s

Examples of Z-Test: P-Value Method

9m 10s

T-Test: One Sample Mean Test

15m 16s

T-Test: Paired Two Sample Mean Test

14m 13s

T-Test : Unpaired Two-Sample Mean Test

17m 6s

Two Sample Proportion Test

14m 43s

Chi-Square Test: Independence Test

12m 57s

Chi-Square Test: Goodness of Fit

6m 51s

ANOVA Test or F-Test

24m 21s

Assignment : Types of Hypothesis Testing

5m 40s

Quiz : Types of Hypothesis Tests

5m

Basics of Linear Regression Analysis

25m 45s

Assumptions of Linear Regression

10m 20s

Multiple Linear Regression Analysis

14m 50s

Quiz : Regression Analysis

4m

Course Summary

4m 30s

Interview Questions

16m 12s

Career Guideline

2m 17s

Normal Distribution

Statistics For Data Science Course Inferential Statistics

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  • Z-Table, T-Table , Chi-Square Table

Course Content

Introduction to Statistics For Data Analysis and Data Science

5m 22s

How to use LearnVern

3m 20s

Fundamentals of Statistics

15m 45s

Basics of Descriptive Statistics

12m 47s

Measures of Frequency

10m 47s

Measures of Central Tendency - Mean

9m 9s

Measures of Central Tendency - Median

4m 48s

Measures of Central Tendency - Mode

5m 21s

Measures of Variability - Mean Absolute Deviation

7m 33s

Measures of Variability - Variance

7m 42s

Measures of Variability - Standard Deviation

10m 36s

Measures of Position

16m

Measures of Shape - Skewness

10m 36s

Measures of Shape - Kurtosis, Box and Whisker Plot

8m 51s

Assignment : Descriptive Statistics

3m 54s

Hypothesis Testing in Data Science

7m 27s

Null and Alternative Hypothesis

9m 6s

Making a Decision - Reject or Fail to Reject Null Hypothesis

9m 21s

Type I & Type II Errors

12m 47s

Covariance and Correlation Coefficients

11m 47s

Types of Correlation Coefficients

15m 49s

Assignment : Hypothesis Testing

3m 53s

Types of Statistical Tests

3m 9s

Z-Test: Critical Value Method

13m 9s

Examples of Z-Test: Critical Value Method

9m 20s

Z-Test: P-Value Method

9m 33s

Examples of Z-Test: P-Value Method

9m 10s

T-Test: One Sample Mean Test

15m 16s

T-Test: Paired Two Sample Mean Test

14m 13s

T-Test : Unpaired Two-Sample Mean Test

17m 6s

Two Sample Proportion Test

14m 43s

Chi-Square Test: Independence Test

12m 57s

Chi-Square Test: Goodness of Fit

6m 51s

ANOVA Test or F-Test

24m 21s

Assignment : Types of Hypothesis Testing

5m 40s

Basics of Linear Regression Analysis

25m 45s

Assumptions of Linear Regression

10m 20s

Multiple Linear Regression Analysis

14m 50s

Course Summary

4m 30s

Interview Questions

16m 12s

Career Guideline

2m 17s

FAQs

The normal distribution, also known as the Gaussian distribution, is a symmetric probability distribution centred on the mean, indicating that data around the mean occur more frequently than data far from it. The normal distribution will show as a bell curve on a graph.

The mean, median, and mode are all equal in normal distributions, which are symmetric, unimodal, and asymptotic. Around its centre, a normal distribution is exactly symmetrical.

The mean of a standard normal distribution is 0 and the standard deviation is 1. The z distribution is another name for this. The symbol N ( μ , σ ) denotes a normal distribution, with N being the mean of the distribution and S denoting the standard deviation of the distribution.

The numbers are evenly distributed both above and below the mean in a normal distribution. If the mean, mode, and median are all equal, the population has a perfectly normal distribution. The mean, mode, and median for a population of 3,4,5,5,5,6,7 are all 5.

Because the probability density graph of the normal distribution resembles a bell, it is commonly referred to as the bell curve. The Gaussian distribution is named after the German mathematician Carl Gauss, who first characterised it.

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