Course Content

Understanding of Data Science

How to use LearnVern

Introduction to Data Measurement in Data Science

Types of Variables in Data Science

Levels of Data Measurement in Data Science

Data Measurement Quiz

Charts and Graphs in Data Science

Frequency Distribution in Data Science

Bar Graphs and Pie Charts in Data Science

Summarizing Quantitative Data in Data Science

Cummulative Distribution in Data science

Histogram and Scatter Plot in Data Science

Cross Tabulation in Data Science

Charts and Graphs Quiz

Measures of Central Tendency and Variability in Data Science

Mean and Percentiles in Data Science

Quartiles in Data Science

Measures of Variability in Data Science

Variance and Standard Deviation in Data Science

Application of Standard Deviation in Data Science

Z-score and Co-efficient of Variation in Data Science

Measures of Central Tendency Quiz

Measures of Central Tendency for Grouped Data in Data Science

Standard Deviation and Variance for Grouped Data in Data Science

Skewness in Data Science

Kurtosis in Data Science

Box and Whisker Plots in Data Science

Measures of Shapes Quiz

Hypothesis Testing in Data Science

Statistical Hypothesis in Data Science

Errors in Statistical Hypothesis in Data Science

Statistical Inference for Single Population in Data Science

Testing Example in Data Science

Statistical Inference with Two Population in Data Science

R Programming in Data Science

Data Types in R in Data Science

Understanding R Console and R Studio in Data Science

Analysis of Variance and Annova in Data Science

Assumption and Variation in One-Way ANOVA in Data Science

Two way ANOVA in Data Science

Summary of ANOVA in Data Science

ANOVA Quiz

ANOVA example in Data Science

One way ANOVA Example in Data Science

Two way ANOVA Example in Data Science

Understanding Datamining in Data Science

Introduction to Simple Linear Regression and Correlation in Data Science

Least Square and Residual Analysis in Data Science

Test assumption of Regression Model in Data Science

Hypothesis and Co-Efficient of Determination in Data Science

Regression Example - Creating Model in Data Science

Residual Analaysis of Model example in Data Science

Residual Analysis of Model Part 2 in Data Science

Residual Analysis of Model Part 3 in Data Science

Regression Quiz

Understanding Clustering in Data Science

Hierarchical Clustering in Data Science

Example of Hierarchial Clustering in Data Science

K Means Clustering in Data Science

Example of K Means Clustering in Data Science

Clustering Quiz

Theoretical Concepts of Dashboard

Creating Pivots and Preparing Charts

Slicers in Dashboard

Preparing Final Dashboard

Presenting Dashboard

One way ANOVA Example in Data Science

Data Science Course Analysis of Variance

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Discussion

Course Content

Understanding of Data Science

How to use LearnVern

Introduction to Data Measurement in Data Science

Types of Variables in Data Science

Levels of Data Measurement in Data Science

Charts and Graphs in Data Science

Frequency Distribution in Data Science

Bar Graphs and Pie Charts in Data Science

Summarizing Quantitative Data in Data Science

Cummulative Distribution in Data science

Histogram and Scatter Plot in Data Science

Cross Tabulation in Data Science

Measures of Central Tendency and Variability in Data Science

Mean and Percentiles in Data Science

Quartiles in Data Science

Measures of Variability in Data Science

Variance and Standard Deviation in Data Science

Application of Standard Deviation in Data Science

Z-score and Co-efficient of Variation in Data Science

Measures of Central Tendency for Grouped Data in Data Science

Standard Deviation and Variance for Grouped Data in Data Science

Skewness in Data Science

Kurtosis in Data Science

Box and Whisker Plots in Data Science

Hypothesis Testing in Data Science

Statistical Hypothesis in Data Science

Errors in Statistical Hypothesis in Data Science

Statistical Inference for Single Population in Data Science

Testing Example in Data Science

Statistical Inference with Two Population in Data Science

R Programming in Data Science

Data Types in R in Data Science

Understanding R Console and R Studio in Data Science

Analysis of Variance and Annova in Data Science

Assumption and Variation in One-Way ANOVA in Data Science

Two way ANOVA in Data Science

Summary of ANOVA in Data Science

ANOVA example in Data Science

One way ANOVA Example in Data Science

Two way ANOVA Example in Data Science

Understanding Datamining in Data Science

Introduction to Simple Linear Regression and Correlation in Data Science

Least Square and Residual Analysis in Data Science

Test assumption of Regression Model in Data Science

Hypothesis and Co-Efficient of Determination in Data Science

Regression Example - Creating Model in Data Science

Residual Analaysis of Model example in Data Science

Residual Analysis of Model Part 2 in Data Science

Residual Analysis of Model Part 3 in Data Science

Understanding Clustering in Data Science

Hierarchical Clustering in Data Science

Example of Hierarchial Clustering in Data Science

K Means Clustering in Data Science

Example of K Means Clustering in Data Science

Theoretical Concepts of Dashboard

Creating Pivots and Preparing Charts

Slicers in Dashboard

Preparing Final Dashboard

Presenting Dashboard

FAQs

One independent variable is used in a one-way ANOVA, while two independent variables are used in a two-way ANOVA. Example of a one-way ANOVA As a crop researcher, you want to see how three different fertiliser combinations affect crop output.

The one-way ANOVA (Analysis of Variance) is a parametric test for determining if three or more groups have statistically significant differences in outcomes. ANOVA looks for a general difference, meaning that at least one of the groups is statistically distinct from the rest.

You'd use ANOVA to figure out how your various groups react, with the null hypothesis being that the means of the various groups are equal. If the difference between the two populations is statistically significant, then the two populations are unequal (or different).

The different types of ANOVA are:

One-Way ANOVA
Two-Way ANOVA
Three-Way ANOVA
General Linear Model.

ANOVA uses an F-test, which tests whether the means of two or more groups are equal. The null hypothesis states that all means are equal, and ANOVA calculates the probability of this happening by using a confidence interval.

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