AP Stat Test 2

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21 Terms

1

Blocking

Grouping already selected subjects into subgroups (blocks) and then randomly assigning each block to treatments.

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2

Purpose of blocking

To reduce variability so that differences can be more easily seen.

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3

Direct control

A method to reduce variability for clearer observation of differences.

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4

Completely randomized experiment design

The most common type of experiment where subjects are randomly assigned to treatments.

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5

Matched pairs experiment

An experimental design where either both treatments are given to a single individual or subjects are matched based on similar characteristics before randomizing treatments.

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6

Point of matched pairs experiments

To reduce within-subject variability.

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7

Control group

A group that receives no treatment, used for comparison against a treatment group.

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8

Placebo

A treatment that appears identical to another but contains no active ingredients, serving as a secret control group.

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9

Single blind

An experimental design where subjects do not know which treatment they are receiving, but the measurers do.

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10

Double blind

An experimental design where neither the subjects nor the measurers know which treatment is being administered, although the experimenter does.

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11

Dot plot

A chart used for displaying numerical data.

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12

Bar chart

A chart used for displaying categorical data.

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13

Mosaic chart

In this chart, each bar's width represents its frequency.

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14

Random selection using random numbers

Choose two numbers at a time, where 01-30 represent people, ignoring 31-99 and repeats until three people are selected.

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15

Number of classes for a histogram

Calculated as the square root of the number of observations.

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16

Class width/intervals

Determined by the formula class width = (high - low) / number of classes.

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17

Left skewed

Another term for negatively skewed data.

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18

Right skewed

Another term for positively skewed data.

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19

Fixing unequal intervals

Achieved by dividing the frequency by the width, known as density.

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20

Bad graphing practices

Poor scaling, such as not starting at zero, can exaggerate differences in graphs.

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21

Scatter plots

Used for displaying bivariate data (numerical data).

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