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Stats 300 > exam 2 (ch 6-8) > Flashcards

exam 2 (ch 6-8) Flashcards

1
Q

two variables to have a distribution

A

bivariate data

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2
Q

when scores on 2 variables are paired

A

bivariate data

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3
Q

a quantitative relationship between two variables

A

correlation

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4
Q

correlation does or does not mean causation?

A

not

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5
Q

what kind of correlation is this: drunkness and motor skills?

A

negative correlation

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6
Q

what kind of correlation is this: coffee intake and energy levels?

A

positive correlation

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7
Q

what kind of correlation is this: hours on videos and length of toes

A

no correlation

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8
Q

two fundamental techniques when it comes to stats

A

correlation and regression

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9
Q

a stat that represents the strength and direction of a relationship between two variables

A

correlation coefficient

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10
Q

correlation coefficient: the value of zero=

A

no relationship

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11
Q

correlation coefiencent: value near -1 or 1 indicates

A

strong relationship

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12
Q

correlation coefficient: values near zero but not zero

A

weak relationship

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13
Q

use to illustrate a correlation

A

scatterplot

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14
Q

the population of variance that two variable share

A

coefficient of determination

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15
Q

coefficient of determination is also known as

A

shared variance or common variance

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16
Q

a stat technique that allows you to make predictions

A

linear regression

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17
Q

correlation is used to establish predictions or relationships?

A

relationship

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18
Q

linear regression operates on what?

A

equation of a line (y=mx+b)

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19
Q

distributions can be broadly categorized as what two things?

A

theoretical or empirical

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20
Q

collecting data and plotting them on a frequency histogram

A

empirical distribution

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21
Q

the distribution of scores from actual data

A

empirical distribution

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22
Q

the distribution of scores one would expect to find

A

theoretical distribution

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23
Q

hypothesized via math logic/ probability

A

theoretical distribution

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24
Q

three types of theoretical distribution

A

normal, binomial, and rectangular distribution

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25
Q

a measure of the likelihood that an event will occur

A

probability

26
Q

probability is at the heart of

A

theoretical distribution

27
Q

distribution in which all scores have the same frequency

A

rectangular distribution

28
Q

equal probability; all scores have the same probability of occurring

A

rectangular distribution

29
Q

distribution of the frequency of events that can have only two possible outcomes

A

binomial distribution

30
Q

bell-shaped theoretical distribution that predicts the frequency of occurrence of chance or random events

A

normal distribution

31
Q

standard deviation units are used to express measurements for what type of scores

A

z scores

32
Q

each trial is asymptotic which means

A

it never touches x axis; it goes on indefinitely

33
Q

A point that separates concave upward or concaves downward

A

inflection point

34
Q

a subset of a specified group

A

samples

35
Q

we use samples because

A

we do not have access to the population usually

36
Q

characteristics of a sample

A

stats

37
Q

entirely of a specified group

A

population

38
Q

characteristics of a population

A

parameter

39
Q

a subset of a population chosen so that each member (item/data point) has an equal probability of being selected

A

random sample

40
Q

best method of sampling

A

random sample

41
Q

a subset of the population chosen such that not all members (items.data points) have an equal chance of being selected

A

bias sample

42
Q

the degree to which your sample is reflective of the population you’re interested in

A

representativeness

43
Q

representativeness can be achieved one of the two ways

A

via sampling technique and via large sample size

44
Q

based on all possible random samples drawn from the same population (using theory of probability)

A

same distribution

45
Q

the mean of sampling distribution

A

expected value

46
Q

standard deviation of a sampling distribution

A

standard error

47
Q

t/f: every sample of a sampling distribution of the mean is carefully selected from the same population size

A

false, it is random

48
Q

t/f: sample size is the same for all samples

A

true

49
Q

t/f: the number of samples is very small, less than 20

A

false

50
Q

t/f: the mean (x bar) is calculated for every sample

A

true

51
Q

the sample means (all the x bar) are arranged into what?

A

a frequency distribution

52
Q

as the sample size increases, the sample distribution looks more like the theoretical normal curve

A

central limit theorem

53
Q

the expected value (x bar of sampling distributions) is equal to

A

standard error

54
Q

t/f: the standard deviation of the sampling distribution is not equal to the standard deviation of the population

A

true

55
Q

if we dont have access to the parameters what can we use?

A

t distribution table

56
Q

any continuous probability distribution that arises when estimating the mean of a normally distributed population in situations where the sample size is small and/or the population standard deviation is unknown

A

t distribution

57
Q

determines the distribution that is most appropriate for your sample size

A

degrees of freedom

58
Q

you need three things to read a t -table

A
  1. a degrees of freedom
  2. determine if it’s 1 or 2 tail
  3. determine the alpha/confidence level
59
Q

the probability you are willing to be correct/incorrect about something

A

alpha level/confidence

60
Q

range of scores that are expected to contain a parameter (i.e. population mean)

A

confidence intervals

Stats 300 (2 decks)

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