Lecture 5 Flashcards

1
Q

What is the rejection region?

A

Set of potential outcomes that lead to the rejection of the null

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2
Q

What is the decision rule?

A

Area where we will decide to reject the null

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3
Q

What is a type 1 error?

A

When you reject the null when the null hypothesis is actually true (denoted as alpha)

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4
Q

How do you read the binomial table?

A

N= number of trials

Numbers on top: Probability of flipping heads in reality

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5
Q

How do you find a rejection region using the binomial table?

A

Keep going down the table until you find a number bigger than alpha, then go back one number

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6
Q

What is a type 2 error?

A

Decreasing alpha will create a possibility that you fail to reject the null, when the null is false (beta)- must have a rejection region smaller than 0.05.

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7
Q

What is power?

A

What kind of power do we have to detect a real effect? What is the probability that we will correctly reject Ho?

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8
Q

How does power increase?

A

With a larger sample size

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9
Q

How does one conduct a power analysis?

A

Establish a value of power before the experiment, use that to calculate sample size. Estimates for alpha and beta, estimates of effect size

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10
Q

What is effect size?

A

An estimate of how large the difference is between sample groups (Based on past research or pilot study)

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11
Q

What does it mean when we have a 95% confidence interval?

A

If i did this study 100 times, the true mean would be within the confidence interval 95 times

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12
Q

When does the P value = 0.01 on a bar graph?

A

When the top of the bottom bar and the bottom of the top bar line up

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13
Q

When does the P-value = less than 0.01 on a bar graph?

A

If there is a gap between the top of the bottom bar and the bottom of the top bar

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14
Q

WWhen does the P value = 0.05 on a bar graph?

A

When the two bars overlap by 1/4.

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15
Q

When does statistical significance happen?

A

When the P-value is less than 0.05, error bars must overlap by 1/4 or less.

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16
Q

What happens to our error bars when we increase the sample size?

A

Error bars get smaller and it eocmes easier to find a possible significant difference.

17
Q

What type of error can a small sample size increase the chance of?

A

Type 2.

18
Q

Why do the error bars get smaller when we increase our sample size?

A

Because bigger samples create more steady means-less variability.