# Get Ready To Tour

October 18, 2008 by kltangen

Filed under 10-Day Tour

#### A University-Level Course.

And It’s Totally Free.

# Day 1: Measurement

October 16, 2008 by kltangen

Filed under 10-Day Tour

Before you conduct a study, use your theory to answer five questions: (1) what are you trying to prove, (2) what is it like in practice, (3) who is predicting whom, (4) who is being studied, and (5) what do the numbers mean? Theories are used to guide research; models are used to test theories. Because theories are composed of constructs, they are untested theoretical realities. But models are built for the purpose of being tested; they are composed of variables.

NOW YOU CHOOSE:

Day 1: Measurement

A Bit More About Measurement

Even More About Measurement 1

Even More About Measurement 2

Even More About Measurement 3

Basic Facts About Measurement

Audio Lectures

Videos

Vocabulary

Quiz 1

Summary

# Day 2: Central Tendency

October 16, 2008 by kltangen

Filed under 10-Day Tour

The goal is to find a way to summarize a large group of numbers. One part of that process is to find a group’s representative. We want one number that will tell us about the entire group. There are 3 basic choices: mean, median and mode. The mean is hypothetical average person. The median is the middle-most person. The mode is the most popular person.

NOW YOU CHOOSE:

Day 2: Central Tendency

A Bit More About Central Tendency

Even More About Central Tendency

More Examples

More Mean Examples

More Median Examples

Median Is Middle Of Distribution

More Mode Examples

Impact of Outlying Scores

On The Mean

On The Median

On The Mode

How To Calculate Central Tendency

Calculating The Mean

Calculating The Median

When There’s No Middle-Most Score

Calculating The Mode

Formulas For Central Tendency

Basic Facts About Central Tendency

Audi: Lectures

Videos

Vocabulary

Quiz 2

Summary

# Day 3: Dispersion

October 16, 2008 by kltangen

Filed under 10-Day Tour

We found the middle of the group because most people score about the same on any variable we measure. Now that you’ve found a representative for the group, how representative is the mean? Is the group unified and nearly everyone has the same score? Or are there wide fluctuations within the group? We want one number that will tell us if the scores are very similar to each other or if the group is composed of heterogeneous scores.

- There are five measures of dispersion:
- Range
- Mean Absolute Deviation (Mean Variance)
- Sum of Squares
- Variance
- Standard Deviation

NOW YOU CHOOSE:

Day 3: Dispersion

A Bit More About Dispersion

Even More About Dispersion

Range

MAD

Sum of Squares

Variance

Standard Deviation

How To Calculate

Range

MAD

Sum of Squares

Variance

Standard Deviation

Formulas For Dispersion

Practice Problems

More Practice Problems

Basic Facts About Dispersion

Audio: Lectures

Vocabulary

Quiz 3

Summary

# Day 4: z-Score

October 16, 2008 by kltangen

Filed under 10-Day Tour

An entire distribution can often be reduced to a mean and standard deviation. A z-score uses that information to indicate the location of an individual score. Essentially, z-scores indicate how many standard deviations you are away from the mean. If z = 0, you’re at the mean. If z is positive, you’re above the mean; if negative, you’re below the mean. In practical terms, z scores can range from -3 to +3.

Day 4: z-Score

A Bit More About z-Scores

Even More About z-Scores

How To Calculate z-Scores

Practice Problems

Basic Facts About z-Scores

Audio: Lectures

Vocabulary

Formulas For z-Scores

Quiz 4

Summary

# Day 5: Correlation

October 16, 2008 by kltangen

Filed under 10-Day Tour

This is the first 2-variable model we’ll consider. Both variables (designated X and Y) are measures obtained from the same subjects. Basically, a mathematical representation of a scatterplot, a correlation indicates whether the variables move together in the same direction (+ correlation), move in opposite directions (- correlation) or move separately (0 correlation). Correlations are widely used to measure reliability, validity and commonality.

NOW YOU CHOOSE:

Day 5: Correlation

Bit More About Correlation

Even More About Correlation

Calculate Correlation

Practice Problems

More Practice Problems

Word Problems

Sim1 Sim2 Sim3

Sim4 Sim5 Sim6

Sim7 Sim8 Sim9

Basic Facts About Correlation

Audio: Lectures

Vocabulary

Formulas

Quiz 5

Summary

# Day 6: Regression

October 16, 2008 by kltangen

Filed under 10-Day Tour

With regression, you can make predictions.

When there is a strong correlation between two variables (positive or negative), you can make accurate predictions from one to the other. If sales and time are highly correlated, you can predict what sales will be in the future…or in the past. You can enhance the sharpness of an image by predicting what greater detail would look like (filling in the spaces between the dots with predicted values). Of course the accuracy of your predictions, depends on the strength of the correlation. Weak correlations produce lousy predictions.

Day 6: Regression

Bit More About Regression

Even More About Regression

Calculate Regression

Practice Problems

More Practice Problems

Word Problems

Sim1 Sim2 Sim3

Sim4 Sim5 Sim6

Sim7 Sim8 Sim9

Basic Facts About Regression

Audio: Lecturs

Vocabulary

Formulas

Quiz 6

Summary

# Day 7: Probability

October 16, 2008 by kltangen

Filed under 10-Day Tour

Moving from describing events to predicting their likelihood involves probabilities, odds, and the use of Fisher’s F test. Probabilities compare of an event to the total number of possible events (4 aces out of 52 cards equals a probability of .077). Odds compare sides: 4 aces in a deck against 48 cards that aren’t aces (which equals odds of 1:12).

Analysis of Regression (ANOR) is an application of probability to linear regression. The ANOR uses a F-test, which is a ratio of variances. It is the ratio of understood variance to unexplained variance. To find the likelihood that a regression can be explained by a straight line, the number derived from an F test is compared to a table of probabilities. If the value you calculated is bigger than (or equal to) the value in the book, the pattern you see in the data is unlikely to be due to chance.

NOW YOU CHOOSE:

Day 7: Probability

Bit More About Probability

Even More About Probability

Even More About ANOR

Calculate ANOR

Practice Problems

More Practice Problems

Word Problems

Sim1 Sim2 Sim3

Basic Facts About Probability

Audio: Lectures

Vocabulary

Formulas

Quiz 7

Summary

# Day 8: Independent t-Test

October 16, 2008 by kltangen

Filed under 10-Day Tour

A t-test asks whether two means are significantly different. If the means, as representatives of two samples of the same variable, are equal or close to equal, the assumption is that the differences seen are due to chance. If the means are significantly different, the assumption is that the differences are due to the impact of an independent variable.

NOW YOU CHOOSE:

Day 8: Student’s t-Test

Bit More About t-Test

Even More About t-Test

How to Calculate t-Test

Practice Problems

More Practice Problems

Word Problems

Sim1 Sim2 Sim3

Sim4 Sim5 Sim6

Sim7 Sim8 Sim9

Basic Facts About t-Test

Audio: Lectures

Vocabulary

Formulas

Quiz 8

Summary

# Day 9: One-way ANOVA

October 16, 2008 by kltangen

Filed under 10-Day Tour

When more than 2 groups are to be compared, multiple t-tests are conducted because of the increased likelihood of Type I error. Instead, before subgroup comparisons are made, the variance of the entire design is analyzed. This pre-analysis is called an Analysis of Variance (ANOVA for short). Using the F-test (like an Analysis of Regression), an ANOVA makes a ratio of variance between the subgroups (due to the manipulation of the experimenter) to variance within the subgroups (due to chance).

NOW YOU CHOOSE

Day9: 1-Way ANOVA

Bit More About 1-Way ANOVA

Even More About 1-Way ANOVA

Calculate 1-Way ANOVA

Practice Problems

More Practice Problems

Word Problems

Sim1 Sim2 Sim3

Sim4 Sim5 Sim6

Sim7 Sim8 Sim9

Audio: Lectures

Vocabulary

Formulas

Quiz 9

Summary