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 Inferential Statistics

5m 3s

Introduction to Probability

17m 26s

Basics of Probability

21m 36s

Probability Distribution

7m 40s

Discrete Probability Distribution

19m 25s

Continuous Probability Distribution

12m 9s

Uniform Distribution

4m 16s

Normal Distribution

10m 18s

Standard Normal Distribution

9m 20s

Log Normal Distribution

3m 49s

Exponential Distribution

5m 33s

Methods to Detect Outliers

9m 26s

Methods to Treat Outliers in Python

15m 42s

Feature Scaling - Normalization V/S Standardization

10m 35s

Sampling Methods

12m 43s

Sampling Distribution

18m 30s

Central Limit Theorem

13m 28s

Assignment : Inferential Statistics

7m 18s

Quiz : Inferential 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

Measures of Frequency

Statistics For Data Science Course Descriptive Statistics

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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 Inferential Statistics

5m 3s

Introduction to Probability

17m 26s

Basics of Probability

21m 36s

Probability Distribution

7m 40s

Discrete Probability Distribution

19m 25s

Continuous Probability Distribution

12m 9s

Uniform Distribution

4m 16s

Normal Distribution

10m 18s

Standard Normal Distribution

9m 20s

Log Normal Distribution

3m 49s

Exponential Distribution

5m 33s

Methods to Detect Outliers

9m 26s

Methods to Treat Outliers in Python

15m 42s

Feature Scaling - Normalization V/S Standardization

10m 35s

Sampling Methods

12m 43s

Sampling Distribution

18m 30s

Central Limit Theorem

13m 28s

Assignment : Inferential Statistics

7m 18s

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 frequency of a data value is the number of times it happens. There are three pupils who work two hours, five students who work three hours, and so on, according to the table. The total number of students in the sample is represented by the sum of the numbers in the frequency column, which is 20.

Frequency Distribution Types:

  • The cumulative frequency distribution is a graph that shows the frequency distribution over time. The frequency distribution is relative. Cumulative frequency distribution in relative terms.

  • Frequency is the number of occurrences in a set. In statistics, frequency is used to measure how often something takes place.
  • "In statistics, frequency is used to measure how often something takes place."
  • This is because frequency can be used as a measurement for counting and measuring events. For example, when we want to know if there are more males or females in a certain group of people, we would use the frequency to calculate the percentage of males and females in that group.

Frequency is a term used to describe how often something occurs. There are different measures of frequency, such as annual frequency, monthly frequency, daily frequency, hourly frequency, etc.

  • Frequency is a measurement that tells us how often something happens.
  • To understand the frequency of a specific event, we can use the following formula:
    Frequency = Number of occurrences / Number of possible occurrences
  • An example of a frequency measurement in statistics would be the number of times an individual has committed a crime in his lifetime.

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