English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 2h 10m | 328 MB
Data isn’t valuable until you put it to good use. Statistics transforms data into meaningful information, enabling organizations to make better decisions and predictions. That’s why statistics—collecting, analyzing, and presenting data—is a valuable skill for anyone in business or academia. This course, part two of a series, continues your training on the fundamentals of descriptive and inferential statistics. Dr. Joseph Schmuller teaches you how to use the tools in Microsoft Excel—statistical functions, 3D maps and charts, the Ideas tool, and the Analysis Toolpak add-on—to carry out more sophisticated statistical analysis. First, learn to visualize sampling distributions. Next, test differences with analysis of variance (ANOVA). Then, find out how to use linear, multiple, and nonlinear regression to analyze relationships between variables and to make predictions. Joe also shows how to perform advanced correlations, test hypotheses about frequencies, and create and run simulations. Once you complete both courses, you should have the foundational knowledge to ace your next exam or interview and perform statistical analyses in the workplace.
Topics include:
- Using statistical functions, charts, and maps in Excel
- Visualizing sampling distributions
- Performing comparisons with ANOVA
- Performing two-way analysis with ANOVA
- Analyzing linear regression
- Performing linear and nonlinear regression analysis
- Forecasting
- Finding advanced correlations
- Testing variable frequencies
- Creating and running simulations
Table of Contents
1 Continuing your data analysis journey
2 Using Excel statistical functions
3 Using the Analysis Toolpak
4 Using statistical charts
5 Using 3D maps
6 Using the Ideas tool
7 Simulating the central limit theorem
8 Visualizing the standard normal and t
9 Visualizing F and chi-square
10 Analyzing between groups ANOVA
11 Performing simple comparisons
12 Performing complex comparisons
13 Performing repeated measures ANOVA
14 Trend analysis
15 Performing two-way ANOVA
16 Making comparisons after two-way ANOVA
17 Visualizing scatter plot and regression line
18 Analyzing the regression line
19 Performing multiple regression
20 Defining natural logs and exponents
21 Performing exponential regression analysis
22 Performing logarithmic regression analysis
23 Performing a power regression analysis
24 Performing polynomial regression analysis
25 Performing logistic regression
26 Forecasting and predicting
27 Performing correlation
28 Comparing two correlation coefficients
29 Performing multiple correlations
30 Performing a partial correlation
31 Testing the independence of two variables
32 Testing goodness of fit
33 Performing Monte Carlo simulation
34 Performing business simulations
35 Next steps
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