Final Flashcards

1
Q

Describes variables and relationships between variables (table 1)

A

Descriptive statistics

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2
Q

Used to determine if an IV has a significant effect on a DV

A

inferential statistics

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3
Q

we use this/these measures of central tendency when analyzing ratio level data

A

mean, median, mode

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4
Q

We use this/these measures of central tendency when analyzing ordinal level data

A

median, mode

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5
Q

We use this/these measures of central tendency when analyzing nominal level data

A

mode

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6
Q

What are the 5 ways to report data?

A
  1. %
  2. % change
  3. rates
  4. ratios
  5. proportions
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7
Q

batting average is an example of reporting data as a:

A

proportion
(# of hits vs. # of a bats)

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8
Q

If there are 25 nurses now, compared to 17 a few years ago, we are looking at the:

A

% change

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9
Q

If looking at divorce, suicide, crime… we look at:
(# of incidents/total population) x 100

This is an example of:

A

rates

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10
Q

if looking at something out of 100,000 people, this is an example of:

A

ratios

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11
Q

these are always between 0 and 1

A

proportions

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12
Q

1 SD from the mean

A

68.2%

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13
Q

2 SD from the mean

A

96%

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14
Q

Represents a comparison of one thing to another

A

ratios

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15
Q

(new-original / original) x 100

A

percentage change

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16
Q

represents the frequency of something for a standard sized unit

A

rates

17
Q

also called Gaussian distribution

A

Normal distribution

18
Q

Represents the distance above or below the mean, in standard deviation units, of any raw value in a distribution

A

z score

19
Q

ranges from -3 to +3

A

z score

20
Q

What are 3 ways to describe the relationship between variables?

A
  1. crosstab analysis
  2. comparison of means
  3. correlations
21
Q

In order to do a chi square, the DV must be ____

A

nominal

22
Q

if you want to figure out what gender of people by certain cars, you would do this type of stat design

A

chi-square

23
Q

when studies that find a significant difference are easier to publish, this is called

A

publication bias

24
Q

Differences among groups for a single IV that are significant, temporarily ignoring all other IVs

A

main effect

25
Q

differences among groups of a single IV that are predictable only by knowing the level of another IV

A

interaction effect

26
Q

When you get a false positive, this is called:

A

type 1 error

27
Q

the degree of risk you are willing to take to reject the null hypothesis when it is true

A

type 1 error