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Psychology 2A > Statistics > Flashcards

Statistics Flashcards

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1
Q

denominator

A

name for the bottom half of a formula

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2
Q

descriptive

A

Statistics that describe an aspect of data (e.g. mean, median, mode, variance, range)

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3
Q

inferential

A

Statistics that allow you to make predictions about or comparisons between data (e.g., t-value, F-value, rho)

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4
Q

interval estimates

A

a range of values that summarise an aspect of a data set. Examples include the range, variance, standard deviation, standard error and confidence intervals.

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5
Q

mean

A

A descriptive statistic that measures the average value of a set of numbers

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6
Q

median

A

The middle number in a distribution where half of the values are larger and half are smaller

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7
Q

numerator

A

name of the top half of a formula

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8
Q

participant

A

the word used to describe someone who has taken part in a study. Note that subject is outdated and no longer used

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9
Q

point estimates

A

a single value that summarises an aspect of a data set. Examples include the mean, median, and the mode.

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10
Q

population

A

All members of a group that we wish to generalise our findings to

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11
Q

sample

A

a subset of the population that you wish to make an inference about through your test

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12
Q

Parametrics

A

Rules or assumptions about the data that must be confirmed before we use a specific test, otherwise the findings would be meaningless. Examples: t-tests, pearson correlation, single regression, multiple regression

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13
Q

Spread

A

Degree of dispersion (variability) of values in a dataset

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14
Q

Range

A

least informative, lowest value to highest value

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15
Q

Interquartile Range

A

summarising values between the 25th and 75th percentile and captures 50% of the distribution

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16
Q

Variance

A

a measure of spread which uses information from all the scores in a dataset - averaged squared deviated from the mean
steps of calculation:
1. Find the difference between value and the mean
2. square the difference
3. sum all the squared differences together
4. Divide by N-1

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17
Q

Standard Deviation (SD)

A

measure of the average deviation from the mean in the original scale, using all the values in the data set
steps of calculation:
1. Find the difference between each value and the mean.
2. Square each difference
3. Sum all the squared differences together
4. Divide by N-1
5. Take the square root

18
Q

Standard Error of the Mean (SEM)/(SE)

A

A statistical measure that describes how much the sample mean is expected to vary from the true population mean
calculated by dividing the SD by the square root of the number of values

19
Q

Probability

A

the likelihood of the occurrence of an event or outcome

p = number of ways the event could arise/number of possible outcomes

20
Q

joint probability

A

the unrelated events occurring at the same time. calculated by multiplying together the probability of each individual event

21
Q

replacement

A

resetting the number of outcomes to the original value after an event occurs

22
Q

Binomial distribution

A

a discrete distribution in which every event has a probability on a given distribution

A statistical distribution that summarises the probability that a value will take one of the two independent values under a given set of parameters or assumptions

23
Q

Normal distribution

A

a theoretical distribution with a particular bell shape. the peak of the distribution corresponds to the mean, mode, median = 0 and the SD = 1

24
Q

Null hypothesis significance testing (NHST)

A

A technique for establishing if a hypothesis is likely based on the probability of finding a value as large as or larger, than the one you have found, if the null hypothesis was true

25
Q

null hypothesis

A

there is no difference or relationship

26
Q

level of significance (alpha)

A

the probability level at which we reject the null hypothesis, usually a = .05

27
Q

Rejection region

A

a portion of a sampling distribution which includes samples with probabilities less than alpha

28
Q

z-score

A

the number of standard deviations any particular score is away from the mean

calculated by subtracting the mean from the value and dividing it by the SD

29
Q

one sample chi-square test

A

method of investigating the probabilities of values being in specific categories/groups. used when dealing with frequencies rather than scores. Assumes independents samples and nominal scale data (categorical data).

30
Q

observed frequencies

A

counts per category, expected: most basic approach is equal likelihood of each option

31
Q

expected frequencies

A

represent a uniform frequency distribution expected under H0 (no preference)

32
Q

degrees of freedom

A

the number of observation (units/data points) that are free to vary to produce a given outcome

for one sample chi square calculated as: k-1 (k is number of conditions)

for cross tabulation chi squares: calculated as (R-1) * (C-1) where R refers to number of rows and C to number of columns

33
Q

effect size

A

a common effect size for the chi quare test is phi. it is a standardised measure of the difference of interest that is comparable across experiments that use different N

34
Q

alpha

A

pre-determined level of significance at which we agree to reject the null hypothesis

35
Q

p (p-value)

A

the probability of finding a test statistic as large or larger than the one found in your study, if the null hypothesis were true

36
Q

cross tabulation chi square tests

A

tests whether variable A and B are related in producing the observed frequency distribution

37
Q

t test

A

inferential test used to compare between two samples/conditions or between one sample and a criteria

38
Q

t value

A

t value is the ratio between two aspects of the data

difference between group means/variability about the group means

39
Q

one sample t test

A

compare one sample against a known test value

Assumptions: interval/ratio data, independent scores, data approximately normally distributed

40
Q

within subjects t test

A

compare two conditions where it is the same participant in each condition

Assumptions: continuous data, difference is normally distributed

41
Q

between samples t test

A

compare two groups or conditions where the participants are different in each group and have not been matched

Assumptions: continuous data, independent scores, approximately normally distributed, homogeneity of variance

42
Q

Order of a results section

A
  1. Restate hypotheses
  2. Check assumptions
  3. Descriptives
  4. Inferentials
  5. Accept/reject hypothesis with Brief interpretation

Psychology 2A (5 decks)

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