week 6 Flashcards

1
Q

What does a small standard deviation

A

the mean is a good representation of the data

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2
Q

What is does a large standard deviation

A

a poor representation of the data

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3
Q

What two types statistics is there

A

Descriptive
Inferential

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4
Q

What is descriptive statistics

A

simply describe data

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5
Q

What is inferential statistics

A

make inferences on data

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6
Q

What are models

A

Model 1: two separate means best account for the data (there is an effect)
Model 2: one mean best accounts for all the data

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7
Q

what is systematic variation

A

the variation that can be explained by the model

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8
Q

What is unsystematic variation

A

the variation that cannot be explained by the model

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9
Q

What is the equation for test satistic

A

Test statistic= variance explained by the model/ variance not explained by the model

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10
Q

What do we do after it is a good model

A

We now calculate the probability of getting this statistic if the null hypothesis is true

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11
Q

How do we calculate probability

A

probability= frequency of the event occurring/ total number of event

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12
Q

What is the alpha

A

the alpha is the probability convention in psychology this is p<0.05
the alpha value is the probability of obtaining a sample statistic than observed, if the null hypothesis was true

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13
Q

What does it mean if the probability is less than the alpha level

A

it is statistically significant

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14
Q

What does it mean if the alpha level is less than the probability

A

it is not statistically significant

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15
Q

What is Beta and what is it

A

Beta=0.2
Beta= is the probability of making a type II error

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16
Q

means for p>0.05

A

we state we have no significant effect
We fail to reject the null-hypothesis

17
Q

Means for P<0.05

A

We state we have a statistically significant effect
we reject the null-hypothesis
Our model is a possible explanation

18
Q

What is a type 1 error

A

incorrect reason to reject the null hypothesis

19
Q

what is type 2 error

A

incorrect reason to fail to reject the null hypothesis

20
Q

What is effect sizes

A

quantitative measure of the magnitude of the experimental effect

21
Q

What is Pearson’s r correlation coefficient

A

high r value means strong relationship between 2 variables
Low r value means weak relationship

22
Q

What is Cohen’s d

A

size of the difference between two means relative to the variability
unlike p-value, not directly affected by sample size
allows comparison of size of effect across studies
recommend to report with t-test and ANOVA