Correlation VS Causation | Insurance Rates | Data Analysis for Beginners Episode #3

We will be doing an end-to-end analysis that covers understanding the underlying levers that drive up insurance costs. This will be done by using traditional statistics. univariate analysis, bivariate analysis, correlation, and regression. This will be an excellent opportunity for you to dive into your linear regression and data analysis tool pack in Excel. Last we will create a data story.
Find the Dataset Here:

Intro
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0:49 Problem Statement
1:36 Insights Development Plan
2:00 Tools and Techniques

Analysis
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3:50 Raw Data Review
5:11 Pivot Charts and Categorical Visuals
13:11 Continuous Variables and Averages
15:55 Box Plots and Univariate Analysis
25:50 Scatter Plots and Bivariate Analysis

Linear Regression:
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32:21 Preparing the Data and Coding Categorical Variables
40:00 Regression Equation
41:40 Regression in Excel
43:00 Regression Output Analysis
44:29 Selecting Coefficient by P-value
46:32 Residuals and Actuals

Data Story
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47:20 Data Presentation

#dataanalysis
#data
#datavisualization
#excel

[absentdata]

Use Count of Children in your pie chart :)

[qasimjan]

Hi Gaelim Holland, thank you for putting up these greate project.

[JancitosInterests]

Very interesting.

But there appears to be a mistake with how many children they have. Because you used "sum of children" instead of "count of children" it appears that there were no one with zero children, but clearly from the Raw Data that was not the case.

Apart from that I really appreciated this presentation. Keep up the good stuff.