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Fall Semester 2024 > Stats Final Exam > Flashcards

Stats Final Exam Flashcards

1
Q

what is an example of a continuous variable

A

age, weight, height

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2
Q

what does correlation describe

A

how variables will co-vary; whether they behave similarly or differently

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3
Q

what symbol expressions correlation

A

pearsons r

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4
Q

what r value indicates no relationship between X and Y

A

0

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5
Q

what is X

A

the predictor

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6
Q

what is Y

A

the outcome

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7
Q

what r values are perfectly correlated

A

1 or -1

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8
Q

what is the expected correlation between variables

A

0

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9
Q

r <= .10 is

A

trivial

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10
Q

r < .30 is

A

small

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11
Q

r< .50 is

A

medium

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12
Q

r >= .50 is

A

large

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13
Q

what is a linear relationship

A

the best way to summarize the trend in the data is with a straight line

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14
Q

what is a quadratic relationship

A

the best way to summarize data is with a curved line

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15
Q

what are the 3 elements of causality

A
  1. correlation
  2. temporal precedence
  3. ruling out alternative explanations
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16
Q

the only reliable method to determine causality is with…

A

experimentation

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17
Q

most correlations are not implying…

A

causality

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18
Q

what does OLS stand for

A

ordinary least-squared regression

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19
Q

what is OLS

A

the smallest distance between Y and Y(hat)

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20
Q

what is Y(hat)

A

predicted value of the constant when x has certain qualities

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21
Q

what does it mean for Y(hat) when a predictor is non-significant

A

that Y(hat) doesnt change as the X value changes

22
Q

what does it mean for Y(hat) when a predictor is significant

A

that Y(hat) changes as X value changes

23
Q

what do you do when you’re asked to estimate an out-of-range value

A

decline! point out the model (OLS) does not allow this

24
Q

what is NOIR with examples

A

Nominal (gender)
Ordinal (military rank)
Interval (temperature C)
Ratio (weight, age, height)

25
Q

continuous data relies on what

A

the mean

26
Q

what does parametric mean

A

they have many underlying assumptions

27
Q

what does non-parametric mean

A

they have fewer underlying assumptions

28
Q

is chi-squared parametric or non-parametric

A

non-parametric

29
Q

if data is continuous, what will likely make an appearance

A

t-tests

30
Q

what is the basic idea of t-tests

A

difference/error

31
Q

chi-squared tests are a calculation of

A

what we expected the answer to be, and what the answer was

32
Q

what is needed for an average

A

mean and standard deviation

33
Q

what does categorical data not have

A

the necessary elements of an average (mean and SD)

34
Q

categorical data can not be…

A

averaged!

35
Q

what are 2 reasons you may use categorical data

A
  1. high variance implies different issues, and converting to categories solves this problem
  2. sometimes group size is too small to facilitate a normal analysis, so we collapse data
36
Q

you cannot go from categorical data to…

A

continuous data

37
Q

what are the two flavours of chi-square tests

A
  1. goodness of fit
  2. tests of independence
38
Q

what is goodness of fit

A

is if data from 1 variable meets expected proportions

39
Q

what is tests of independence

A

describe if there is a non-random association between 2 variables

40
Q

what are 2 basic assumptions of chi-square

A
  1. independence of observations
  2. size of expected frequencies
41
Q

what is independence of observations (chi-sqaure)

A

persons can only give data for one cell (ex. name) theres only one answer

42
Q

what are some examples of GOF tests

A
  1. are men/women equally likely to be lawyers
  2. are Canadian university professors more likely to be a non-minority
  3. are left-handed people more likely to be divorced
43
Q

what must be known for GOF

A

only makes sense is proportions are known; need a baseline

44
Q

what are all GOF tests based on

A

general population

45
Q

what is fe

A

frequency of expected

46
Q

tests for independence uses….

A

frequency data to evaluate the relationship between two variables

47
Q

what does effect size describe

A

the magnitude of difference between groups; extent to which the null hypothesis is incorrect

48
Q

what is cramer’s V

A

a statistic to calculate the effect size of chi-square

49
Q

what type of effect size to be want

A

large

50
Q

what changes the standards for small, medium, and large effect sizes

A

degrees of freedom

Fall Semester 2024 (6 decks)

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