- By
**vala** - Follow User

- 298 Views
- Updated On :

Variability. Chapter 4. What is it?. How much difference there is from person to person How spread out scores are No variability = all scores are the same. Why do we care?. Less variability = more know about the population based on the sample

Related searches for Variability

Download Presentation
## PowerPoint Slideshow about 'Variability' - vala

**An Image/Link below is provided (as is) to download presentation**

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

### Variability

Chapter 4

What is it?

- How much difference there is from person to person
- How spread out scores are
- No variability = all scores are the same

Why do we care?

- Less variability = more know about the population based on the sample
- Less variability = more any one person can tell you about the group that he or she is from

To keep in mind

- Two groups of scores can have the same mean, but different amounts of variability
- Two groups of scores can have different means, but the same amount of variability
- mean and variability measure two different things

Quantifying variability

- Range = number of scores between the highest and lowest scores
- Problem = only the highest and lowest scores matter
- Outlier high range

- Can use interquartile range instead, which just addresses number of scores between highest and lowest, once top and bottom 25% have been lopped off
- Still not as good of a measure as we’d like to use

- Problem = only the highest and lowest scores matter

Standard Deviation

- Ideal measure of variability
- Tells about average distance of scores from mean
- i.e., how much do scores deviate from the mean of the group

- Keep in mind: standard deviation tells about all the scores

Calculating standard deviation

- Most straightforward:
- Take each score, subtract the mean
- Take the mean of those difference scores

- Problem: always get zero

To avoid zero

- First calculate variance (average squared distance of each score from the mean)
- 1. take each score, subtract the mean
- 2. square that difference
- 3. add up across all scores
- sum of squares (sum of the squared difference between each score and the mean, SS)
- 4. divide

Divide by what?

- Depends on who you have information from
- If you have information from all the people you care about, divide by the total number of scores you have (n)
- s2 = variance

- If you have information from a sample, but want to estimate variability for the population, divide by one less than the total number of scores you have (n-1)
- n-1 = df = degrees of freedom
- s2 or SD2 = variance

What about standard deviation?

- To get from variance to standard deviation, want to get from average squared distance between each score and the mean to the average distance between each score and the mean
- regardless of whether using formula for population or for sample, take the square root
- s or s (or SD)

What is s, or SD, exactly?

- Estimate of how much variability there is in the population, based on how much variability there is in the sample
- Will not be exactly the same, but will give a good estimate

Be sure to keep in mind

- What, in English, are:
- Sum of squares
- Variance
- Standard deviation

- How to calculate, for population, and to estimate in a population based on the sample
- Symbols
- What it all means

Download Presentation

Connecting to Server..