Science Research & AP Stats Integration

SUMMARY OF STATISTICAL CONCEPTS PRESENTED

EXPERIMENTAL DESIGN

This is merely a supplement to the Science Research version of this curriculum

Focuses on Control Variables and some basic design concepts

Also explores Sampling Design, which constitutes different methods to collect the samples to be used in an experiment or different ways to assign the treatment

LURKING VARIABLES

A lurking variable is a variable that isn’t being studied but impacts the result of the experiment

Discusses what a lurking variable is and it’s effect on experiments

Discusses the different situations that arise from lurking variables

Attempts to get students thinking of ways to control lurking variables.

NUMERICAL REPRESENTATIONS

Discusses the differences between Mean, Median, and Mode as measures of average

Discusses when to use the correct measure of average

Discusses measures of spread, their meaning, and how they effect data

Examines specifically standard deviation and 5 # summary & IQR as measures of spread

LINEAR REGRESSION

Describes how to find and equation of least squares (line of best fit), what the variables mean in context, and how to use the equation to make predictions

Discusses how to use the r & r2 values to discuss the strength of the linear relationship between 2 variables

Discusses how to make residuals and residual plots and how to use them to identify the proper relationship between the data

NON-LINEAR REGRESSION

Examines what to do if the relationship is not linear

Looks at using Exponential and Power models for non-linear data

Reviews and reinforces the importance of residual plots

Examines how to use these new equations to make predictions

HYPOTHESIS TESTING

Discusses the uses and processes behind hypothesis testing

Works through the step by step process of performing a general hypothesis test

Discusses statistical significance and it’s importance when making experimental conclusions with data

Also briefly examines the different types of tests and when they could be used in Research

T-TESTING & 2-SAMPLE T

Looks at when and how to use a t-test when testing for averages

Discusses the specifics to a t-hypothesis test, the conditions needed, and how to specifically use the t-tables to make statistical decisions

Looks at when to use and how to use 2-sample t-tests (when comparing two means) and the difference between a 2-sample and matched pairs test

LINEAR REGRESSION T-TEST

Reviews the concepts of linear regression

Discusses the difference between an equation for individuals and an equation for averages

Shows how to test if the relationship between two variables is STATISTICALLY significant

CHI SQUARE TESTING

Chi Square Goodness of Fit and 2-way Table testing would mainly be used in genetics

Due to lack of actual genetic examples, these shows simply show the mechanics of the tests and how they are often used in statistics

These tests are used to test whole distributions at once, but are NOT to be used to test more than 2 means