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Microsoft Excel 2003 for Statistics Course

Microsoft Excel 2003 for Statistics Course

Microsoft Excel is the world’s best-selling mathematical application, one that is installed on nearly every business computer out there. Although not a statistical application, Excel can perform many basic statistical tasks, from computing simple descriptive statistics such as mean and standard deviation, to complex regression analyses, chi-squared and t tests, and Analysis of Variance (ANOVAs). Join Mark and Beth Clarkson as they introduce you to the basics of statistics, statistical analysis, and statistical graphing with Microsoft Excel. Each step along the way is illustrated with real-world situations. You can start learning right now by clicking one of the movie topics below.
Generating Random Data
Patterns / Dates / Uniform Distribution
Binary / Bernoulli / Normal Distribution
Poisson & Custom Distributions

Probability Terms & Definitions – Lesson 1
Probability Terms & Definitions – Lesson 2
The Laws of Probability
Computing Independent Probabilities – Lesson 1
Computing Independent Probabilities – Lesson 2
Computing Dependent Probabilities
Selecting a Random Sample: Set Up
Selecting a Random Sample: Execution
Sampling from a List – Lesson 1
Sampling from a List – Lesson 2
Sampling an Existing Database – Lesson 1
Sampling an Existing Database – Lesson 2
Adding Data to an Existing Database

Descriptive Statistics
The Default Histogram
Improving the Histogram with Custom Bins
Creating Descriptive Statistics
Using Inline Functions
A Histogram of 2006 Restaurant Bills
Unconfounding The Data – Lesson 1
Unconfounding The Data – Lesson 2
The Pareto Chart – Lesson 1
The Pareto Chart – Lesson 2

Computing Probabilities w/ Distributions
Using the Binomial – Lesson 1
Using the Binomial – Lesson 2
Using Compliments
Using the Poisson
Building a Histogram
When to Use the Normal Distribution
Computing Probabilities with Normdist()
Norminv() / Normal vs. Poisson

Relationships in Anscombe’s Data
The Types of Graphs in Excel
Pivot Tables & Pivot Charts
Scatter Diagrams
Pivot Tables with Multiple Variables
Pivot Tables & Pivot Charts – Lesson 1
Pivot Tables & Pivot Charts – Lesson 2
Chi-Squared: Getting Ready
Chi-Squared: How Chi-Squared Works
Chi-Squared: Expected Values
Chi-Squared: Computing Expected Values
Chi-Squared: Summarizing the Data
A 2nd Chi-Squared Test – Lesson 1
A 2nd Chi-Squared Test – Lesson 2
Finishing Our 2nd Chi-Squared Test
Intro to Correlation
Your First Correlation In Date & Bill
Computing More Correlations

Graphical analysis
Improving Our Histogram
Reformatting Our Scatter Chart
Formatting Axes & Finishing Touches
Other Chart Options
Graphing Multiple Variables
Multiple Variables: The Plot Area
Multiple Variables: Lines & Ordering
Multiple Variables: Axes & Titles

Inferential Statistics – Regression
The Trend Line
R-Squared & the Regression Equation
Regression: R-Squared & Significance
Coefficients & Residuals
Residual & Line Fit Plots
Making Predictions
Identifying Data Sets for Regression
The Pivot Table – Lesson 1
The Pivot Table – Lesson 2
Regression by Total Bill
Regression by Average Bill – Lesson 1
Regression by Average Bill – Lesson 2
Regression by Type
Banquet Estimates
Estimating Our Error
Buffet Estimates

Inferential Statistics in ANOVA
t-Test: Setting Up the t-Test
t-Test: Consulting Our Pivot Table
t-Test: Running the t-Test
t-Test: Interpreting the Results
ANOVA: Introduction
ANOVA: Preparing the Data
ANOVA: Running ANOVA & Checking Variances
ANOVA: Interpreting the Results
ANOVA: Understanding the Statistics
Graphing the Confidence Intervals
Computing the Confidence Intervals

Wrap-up & Review
Data Classes / Validation / Distributions
Generating Data & Probability Concepts
Histograms & Descriptive Statistics
Pivot Tables / Chi-Squared / Correlation
Improving Graphs & Linear Regression
t-Test & ANOVA


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