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Year 2 - Semester 1 > KNPE 251 2/2 > Flashcards

KNPE 251 2/2 Flashcards

(71 cards)

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1
Q

Alternative Hypothesis

A

a statement, or position that is the positive viewpoint of your research question

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2
Q

directionality

A

whether there is direction in the hypothesis

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3
Q

null hypothesis

A

a statement or position, that is the skeptical viewpoint of your research question

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4
Q

Alpha (type I error)

A

probability of rejecting null when it is true

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5
Q

p-value

A

is the probability of seeing your data or something more extreme under the null hypothesis

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6
Q

statistical significance

A

is the conclusion that a set of data are unlikely to come from the null hypothesis

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7
Q

false negative

A

tests are negative when it should be positive

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8
Q

false positive

A

test results are positive when they should be negative

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9
Q

Type II error

A

probability of failingto rejective the null hypothesis when it is false

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10
Q

Single-sample T test

A

a statistical test that compares a sample mean of a numerical variable to a reference value. The null distribution is a t- distribution

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11
Q

Paired measurements

A

are two measurements taken from the same sampling unit

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12
Q

paired-sample t test

A

is a statistical test that compares the difference between paired measurements of a numerical variable to a reference value. The null distribution is a t- distribution

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13
Q

two-sample t-test

A

is a statistical test that evaluates whether the mean of a numerical variable for one group is different from the mean of another group. the null distribution in a t-distribution

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14
Q

expected contingency table

A

table of expected frequencies under the null hypothesis

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15
Q

independence In contingency tables

A

refers to the cells in the table having equal relative proportions across the levels of each variable independently

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16
Q

interaction in contingency tables

A

refers to the cells in the table not having equal relative proportions across levels of each variable

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17
Q

chi-squared distribution

A

the distribution of chi-squared scores expected from repeatedly sampling a statistical population where the null hypothesis is true. It is the null distribution for hypothesis testing with categorical data

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17
Q

chi-squared test

A

is a hypothesis test used with categorical data

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18
Q

chi-squared score

A

is the measure of the distance between two contingency tables. If the contingency tables are an observed and expected table, then measures the distance between sample data and the null hypothesis

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19
Q

X^2

A

the measure of difference between two contingency tables

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20
Q

association

A

is a pattern whereby one variable increases (or decreases) with a change in another variable. There is no implied causation between the variables

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21
Q

Bivariate normal distribution

A

is a normal distribution for two numerical variables that can be used to describe a statistical population where there is an association between the variables. Often used to describe the set up for correlation tests

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22
Q

correlation coefficient

A

the statistical test used to evaluate a sample correlation coefficient against a null hypothesis

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23
Q

correlation test

A

is a measure of association between two numerical variables.

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24
p=-1 (correlation coefficient)
perfect negative association
25
p=0 (correlation coefficient)
no association
26
p=1 (correlation coefficient)
perfect positive association
27
Pearsons correlation coefficient
is the statistical test used to evaluate a sample correlation coefficient against a null hypothesis
28
r
is the statistical test used to evaluate a sample correlation coefficient against a null hypothesis
29
dependant variable
response variable
30
independent variable
predictor variable
31
intercept
value of the response variable when the predictor variable is zero
32
Linear regression
statistical test used to evaluate whether changes in one numerical variable can predict changes in another numerical variable
33
link function
one of three parts of linear regression; connects the systematic component to the random component
34
predictor variable
numerical variable used to predict the response variable
35
random component
one three parts to linear regression; describes the probability distribution for sampling error
36
residual
the difference between the observed data point and the predicted value
37
residual variance
average squared residual value across all data points
38
response variable
numerical variable predicted by the predictor variable
39
slope
the parameter in a linear regression that describes the amount that the response variable increases (or decreases) for every unit change in the predictor variable
40
statistical model
a mathematical model that incorporates both the relationship among variables and how the data are generated
41
sum of squares
another name for the residual variance of linear regression
42
systematic component
one of three parts of a linear regression; describes the mathematical relationship that connects the predictor variable and the response variable
43
heteroscedasticity
term used to describe residual patterns that are not homoscedastic
44
homoscedasticity
an assumption of a linear regression stating that the residuals have equal variance across the predictor variable
45
independence (assumption)
an assumption of linear regression stating that the residuals sequentially independent from each other
46
Linearity (assumption)
an assumption of linear regression stating that the response variable is a linear function of the predictor variable
47
Normality (assumption)
an assumption of linear regression stating that the residuals are not normally distributed
48
Shapiro-Wilks test
statistical test to quantitatively evaluate the assumption that the residuals are normally distributed
49
F
used in the F-test to quantify the ratio of two variances
50
F-score
used in the F-test to quantify the ratio of two variances
51
F-test
statistical hypothesis test used to evaluate whether the variances of two groups are different
52
analysis of variance (ANOVA)
common name given to statistical tests based off the F-distribution
53
group variation
the variation between the group means and the overall grand mean
54
residual variation
the variation between the sampling units and the group means
55
contrast statement
A test of the difference in means between two groups in an ANOVA
56
Family of contrasts
the set of all contrast statements used for a set of data
57
family-wise error rate
the type I error rate for the family of contrasts
58
post hoc tests
secondary tests uses to evaluate what groups have different means in an ANOVA
59
Turkey HSD test
A type of post hoc test that evaluates all possible contrast statements
60
Additivity
when the response to the combination of two levels is simply the sum of the two
61
cell
the group of sampling units that corresponds to the joint level of two categorical variables
62
interaction
when the response to the combination of two levels is not the simple sum of the two
63
interaction plot
a specialized plot that highlights the interaction pattern between two categorical variables
64
Main effects
another name for a categorical variable in a two-factor ANOVA
65
two-factor analysis of variance
two-factor ANOVA statistical test used to evaluate the change in a numerical across two categorical variables
66
Sources of Variation
are the partitioning of the data set by factor means, interactions and residuals that form the basis of F-tests
67
If the p value is greater than or equal to alpha we...
fail to reject null hypothesis
68
if p value is less than alpha we...
reject null hypothesis
69
tradeoff between error rates type I and II
when one increases the other decreases, they are inversely related
70

Year 2 - Semester 1 (6 decks)

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