Flashcards in Chapter 8- Confidence Intervals, Effect Size and Power Deck (15):

1

## What is a point estimate?

### A point estimate is a sample statistic that is just one number used as an estimate of the populaton parameter

2

## What is an interval estimate?

### An interval estimate is a sample statistic that provides a range of plausible values for the populaton parameter

3

## What is a confidence interval?

### A confidence interval is an interval based on the sample statistic that includes the population mean a certain percentage of the time, if we were to sample from the same population repeatedly (95 percent of the time),

4

## What is effect size?

### Effect size indicates the size of a difference and is unaffected by sample size. It tells how much two populations DO NOT overlap. The less the overlap, the bigger the effect size.

5

## What are two ways the effect size can be decreased?

### The two ways the effect size can be decreased is a) if their means are farther apart, b) variation within populatoin is smaller

6

## To fairly compare distributions, what populations should be we look at?

### To fairly compare distributions, we should look at population distributions because the bigger sample will create a skinnier distribution

7

## What happens when the sample size increases?

### When the sample size increases, the test statistic becomes more extreme and it becomes easier to reject the null hypothesis

8

## Effect sizes are calculated with respect to _____

### Effect sizes are calculated with respect to scores rather than means so are not congruent on sample size

9

## What is Cohen's d?

### Cohen's D is a measure of effect size that compares the difference between means in standard deviation units of the population

10

## What are the rule of thumb effect sizes

### 0.2 small, 0.5medium and 0.8 large

11

## How is Cohen's d calculated?

### Cohen's d is calculated by observed mean- means divided by SD

12

## What is Power?

### Power is the probability that we will reject the null hypothesis , if the null hypothesis is false. In other words, our likelihood that we will detect an effect if its really there

13

## When is power calculated?

### Power is ideally calculated before the study is run to help determine how many participants to collect in order too detect an effect

14

## Ideally what percentage of power do you want?

### About 80

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