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THE STATS4STEM TEAM

Numerical Measures & Graphics
Measures of Center
Standard Deviation – Measures of Spread
Percentiles – Quartiles – IQR –

5 Number Summary
Boxplots
Histograms
Stem-And-Leaf
Ogive Plots
Describing Distributions

Technology
TI - Calculating Numerical Summaries
TI - Boxplot and Histograms

R - Calculating Numerical Summaries
R - Histograms
R - Boxplots
R - Stem-And-Leaf

Normal Distribution
Intro To the Normal
Constructing the Normal Density Curve
Emperical Rule Link
TI - Normal Distribution Calculations

R - Normal Distribution Calculations
Assessing Normality
Normal Distribution – Solving for x

Linear Transformations

Linear Regression
Scatterplots
Correlation
Fitting Linear Model (TI-83 or R)
Assumptions for using Linear Regression
Residuals & Residual Plots
Outliers and Influential Observations
Inference – Linear Regression
Linear Regression Applet
Confidence Interval – Linear Regression
Animation – Confidence Interval Linear Regression
Hypothesis Test – Linear Regression
Interpreting Linear Regression Computer Output
Linear Regression – Formula Calculations

Non-Linear Regression
Exponential Growth
Power Law

Design of Experiments & Surveys
Designing an Experiment

Probability
Introduction to Probability
Probability Rules & Terms
Probability - Independence
Conditional Probability

Discrete and Continuous Random Variables
Difference between Discrete & Continuous
* Density Curves
Calculating the Mean & Standard Deviation of Discrete Random Variables
* Rules for Means and Variances

Binomial & Geometric Distributions
Binomial Distribution
Binomial Distribution – CDF Function
Normal Approximation – Binomial Distribution
Geometric Distribution

Sampling Distributions
Difference Between Statistics and Parameters
* Sample proportions
* Sample means

Central Limit Theorem
* Sampling Animation – Only Normal Data
* Biased and Unbiased Estimators

Inference
Introduction to Hypothesis Testing
Relationship Between P-value and Conclusion
Type 1 and Type 2 Errors – Hypothesis Testing

1 Sample Mean
Confidence Interval – 1 Proportion
Confidence Interval – 1 Sample Mean (z)
Reading the t-table – z*
Confidence Interval – 1 Sample Mean (t)
t-distribution
Reading the t-table – t*
Confidence Interval – Difference of Means
Confidence Interval – Matched Pairs
Confidence Interval – Difference of Proportions
Sample Size Calculation – 1 Proportion
Sample Size Calculation – 1 Sample Mean
Hypothesis Test – Conclusion
Hypothesis Test – 1 Sample Mean (z)
Hypothesis Test – 1 Sample Mean (t)
Hypothesis Test – Difference of Means
Hypothesis Test – Matched Pairs
Hypothesis Test – 1 Proportion
Hypothesis Test – 2 Proportions
Chi-Square Distribution
Chi-Square – Goodness of Fit
Chi-Square Test of Association
Chi-Square Test of Homogeneity