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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

Statistical Inference with Two Population in Data Science

Data Science Course Hypothesis Testing

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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

Statistical inference can be divided into two categories: statistical estimating and statistical hypothesis testing.

Statistical inference is the process of inferring attributes of an underlying probability distribution via data analysis. By testing hypotheses and producing estimates, inferential statistical analysis infers properties of a population.

Inferential statistics allows you to create predictions ("inferences") from data (for example, a chart or graph). Descriptive statistics describes data (for example, a chart or graph). Inferential statistics are used to generate generalisations about a population using data from samples.

Statistics can be divided into two types: (1) descriptive statistics and (2) inferential statistics.

The population of inference is the population (or universe) to which a sample survey's conclusions are supposed to generalise. Surveys are used to investigate demographic characteristics and establish broad generalisations.

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