Chapter 8- Confidence Intervals, Effect Size and Power Flashcards

1
Q

What is a point estimate?

A

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

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2
Q

What is an interval estimate?

A

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

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3
Q

What is a confidence interval?

A

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),

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4
Q

What is effect size?

A

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.

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5
Q

What are two ways the effect size can be decreased?

A

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

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6
Q

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

A

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

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7
Q

What happens when the sample size increases?

A

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

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8
Q

Effect sizes are calculated with respect to _____

A

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

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9
Q

What is Cohen’s d?

A

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

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10
Q

What are the rule of thumb effect sizes

A

0.2 small, 0.5medium and 0.8 large

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11
Q

How is Cohen’s d calculated?

A

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

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12
Q

What is Power?

A

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

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13
Q

When is power calculated?

A

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

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14
Q

Ideally what percentage of power do you want?

A

About 80

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15
Q

What are 5 ways to increase Power?

A

The five ways to increase power is 1) increase alpha (cut off value- rarely used), 2) Used one tailed test 3) increase sample size 4) increase effect size 5) decrease standard deviation

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