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Stats 101 > Final > Flashcards

Final Flashcards

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1
Q

What is the “who”

A

Study units or simply who the subjects or participants are

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2
Q

Sample

A

representative sample of a target population

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3
Q

parameter

A

measure of a population

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4
Q

statistic

A

measure of a sample

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5
Q

explanatory or predictor variables

A

independent variables

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6
Q

response variable

A

dependent variable

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7
Q

extraneous variables

A

explanatory variables that are not of interest that could affect the response variable

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8
Q

systematic sampling

A

First-person is selected randomly

Then Every [period of time]

Then Every nth person

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9
Q

Stratified vs cluster

A

Stratified: Population is divided into groups based on prior information. Then within each group random sampling is done. Alberta example

Cluster: Randomly select groups of people and then all people within these groups are interviewed.

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10
Q

Voluntary response bias

A

Asking for volunteers but people who like something are more likely to volunteer

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11
Q

Response bias

A

Loaded questions: Questions suggest or prompt a particular response favored by the researcher

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12
Q

Nonresponse bias

A

Large amount of people fail to respond to questions

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13
Q

Difference between observational and experimental studies

A

In observational studies, there is no manipulation or control of variables/conditions. In experiments there is deliberate manipulation of explanatory variables

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14
Q

Observational studies population and casual inferences

A

Population inferences: Can be made with random selection

Casual Inferences: Can NOT be made as there is too many extraneous variables. cause and effect cannot be made

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15
Q

Experimental studies population and causal inferences

A

Both can be made if there is random selection and random assignment

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16
Q

Relative frequency

A

Frequency divided by total number of observations

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17
Q

Pie Chart

A

Frequency of categorical data

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18
Q

Bar Graph

A

show the frequencies for one variable

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19
Q

Marginal and joint distribution

A

Marginal: Total frequency for each variable

Joint: Frequency of joint event

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20
Q

Conditional distribution

A
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21
Q

Negative skew vs positive skew

A
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22
Q

Median and mean resistance

A

Median is resistant to extreme values or skewness

Mean: is NOT resistant because it is influenced by skewness

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23
Q

Skewed distribution best measure of centre and spread

A

Centre: Median

Spread: Quartiles

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24
Q

Symmetric distributions best measure of centre and spread

A

Centre: Mean

Spread: Standard deviation

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25
Q

Mean mode and median in right/positive skewed

A

Mode < Median < Mean

RODE

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26
Q

Mean mode ande median in left/negative skewed

A

Mean < Median < Mode

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27
Q

If there is an odd set of observations is the median included

A

no

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28
Q

Boxplots parts

A
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29
Q

Population standard deviation

A
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30
Q

Boxplots skew

A
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31
Q

Quartiles skew

A
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32
Q

Probability for at least one

A
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33
Q
A
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34
Q

Sample size for normal distribution

A

> 30

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35
Q

between a small sample and a large sample, when sampling is taken, which has more variability

A

smaller sample has more variability

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36
Q

Calculating quartiles

A
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37
Q

height calculation for a uniform distribution

A
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38
Q

The variance between two values

A
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39
Q

finding z or probability for sample mean

A
40
Q

probability or z score for a sample proportion

A
41
Q

assumption of normality for proportion

A
42
Q

central limit theory

A
43
Q

mean for two points

A
44
Q

Probability between two points sometimes on a rectangle

A

This finds the actual probability not the z score

45
Q

Type I error

A

Accidently rejecting null hypothesis

You thought there was a difference when there wasn’t one

Alpha

46
Q

Type II error

A

Not rejecting the null hypothesis when you should have

You thought there was no difference when there was one

beta

47
Q

To reject the null hypothesis is p greater then or less than alpha

A

p<alpha

48
Q

What does alpha mean

A

The maximum probability of the type I error that you will allow for

49
Q

what does the p value mean

A

Observed probability of a type 1 error that you will find

50
Q

Margin of error one proportion

A
51
Q

What does the p value mean in proportions

A
52
Q

When to reject the null hypothesis in a one-population proportion test

A

the hypothesized proportion is not within the confidence interval

53
Q

Determining sample size

A
54
Q

two population proportions rejecting the null hypothesis

A
55
Q

Chi squared expected frequency calculation

A
56
Q

when do you double the p-value

A

in z score when it is two tailed

don’t forget to subtract from 1 if its positive

57
Q

How to calculate margin of error

A

alpha/2 multiplied by SE

so confidence interval without estimate

58
Q

When to reject the null hypothesis for one population mean

A
59
Q

what does sp mean

A

pooled standard deviation

60
Q

when to use paired t test

A

Ecological monitoring

Medical measurements from the same patient

Taking measurements from the same area

61
Q

what does k and n mean in anova

A

k means number of populations

n means total number of observations (x)

62
Q

how to find pooled standard deviation in anova

A
63
Q

How to find F statistic in ANOVA

A

on formula sheet

mean square of between groups
___________________________________
means square of within groups

64
Q

relationship between sum of squares, df, and mean square

A
65
Q

What does a linear regression measure

A

relationship between two quantitative variables

66
Q

How to determine the strength of a linear relationship

A

r close to -1 or 1 means a strong linear relationship

r close to 0 indicates none or weak relationship

67
Q

how to calculate r

A
68
Q

units of r

A

no units as they cancel out during calculations

69
Q

interpolation vs extrapolation

A
70
Q

coefficient of determination

A

r squared

71
Q

How to tell if two events are independent

A

If P(A∩B) is the same as P(A) times P(B) then the events are independent

72
Q

Chi square tests

A
73
Q

Chi square independence test hypothesis

A
74
Q

Assumptions for a one/two proportion z test

A
  1. All samples are taken independently
  2. The number of failures and successes are both at least 10
75
Q

Properties of chi square curves

A

one tailed

always positive

76
Q

CHi square assumptions

A
  1. simple random sampling
  2. indpendent sample
  3. sample size should be no more than 10% of population
  4. all expected frequencies are at least 5
77
Q

properties of a t-curve

A
78
Q

margin of error and sample size

A

inversely proportional

79
Q

Properties of a F curve

A
80
Q

Disjoint

A

Events are considered disjoint if they never occur at the same time; these are also known as mutually exclusive events.

Events are considered independent if they are unrelated.

81
Q

The level of significance in a hypothesis test is?

A

The probabililty of rejecting a null hypothesis when it is in fact true

82
Q
A
83
Q
A
84
Q
A
85
Q
A
86
Q
A
87
Q
A
88
Q

probability for mean

A
89
Q

probability for mean

A
90
Q

probability for proportion

A
91
Q

what is the assumption of equal variance?

A

When the SD divided are under 2

92
Q

how to find the best estimate of standard deviation or the best estimate of common variance?

A

Square root of MSe
in lab this is the squared root of the residual

93
Q

assumption of equal variances for an anova test

A

the F-test is valid as long as the largest standard deviation is no more than
twice the smallest standard deviation

94
Q

how to find the sum of squares or ss

A
95
Q

how to find the sum of squares/ss error or residual

A

Stats 101 (2 decks)

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