Test #1 Flashcards

0
Q

Variable

A

Any characteristic of a case

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1
Q

Cases

A

The subjects of a data set (objects or people)

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2
Q

Histogram

connected

A

Compares the values of different items, uses quantitative variables

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3
Q
Bar chart
(not connected)
A

Compares the values of different items, uses categorical variables

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4
Q

Ways to describe a bar chart/histogram

A
  1. Shape
  2. Center
  3. Spread
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5
Q

Outlier

A

Any value that falls outside the overall pattern, can affect mean and standard deviation

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6
Q

Mode

A

The most common value in a data set, the major peaks of a bar chart/histogram

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7
Q

Symmetric

A

Distribution creates a mirror image

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8
Q

Skewed

A

Distribution is concentrated to the left or right

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9
Q

Shape

A

Symmetric vs. skewed

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10
Q

Center

A

Mean vs. median

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11
Q

Spread

A

Standard deviation vs. IQR

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12
Q

Categorical variables

A

Data is words, places cases into categories

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13
Q

Quantitative variables

A

Data is numbers, measures the values of each case

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14
Q

Median

A

The middle value or midpoint of a distribution

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15
Q

Mean

A

The average value of a distribution

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16
Q

Best ways to describe a distribution

A

Measure of center and measure of spread

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17
Q

Q1

A

The median of the data which fall to the left of the overall median

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18
Q

Q3

A

Median of the data which falls to the right of the overall median

19
Q

Five-number summary

A
Min
Q1
Median
Q3
Max
20
Q

Boxplot

A

A graph of the five-number summary

21
Q

IQR

A

Q3 - Q1 (the distance between the quartiles)

22
Q

Standard deviation formula

A

S = square root of: 1 / number of cases - 1 E (x1-mean)squared

23
Q

Standard deviation

A

How much distance there is from the mean, greater than 0.

24
Normal distribution
Bell curve, symmetric, unimodal | N(mean, standard deviation)
25
Unimodal
A distribution that contains one single peak
26
68-95-99.7 rule
68% of observations fall within 1 standard deviation of the mean 95% fall within 2 SD of the mean 99.7% fall within 3 SD of the mean
27
Z-score
Standardized value of x
28
Z-score formula
z = x - mean / standard deviation
29
Proportion
Decimals
30
Response variable (y- axis)
Dependent variable, measures outcome
31
Explanatory variable (x-axis)
Independent variable, explains or causes the change in the response variable
32
Scatterplot
Shows the relationship between 2 quantitative variables measured on the same individuals
33
Ways to describe a scatterplot
1. Form 2. Direction 3. Strength
34
Form
Linear
35
Direction
Positive vs. negative vs. none
36
Strength
Strong vs. weak
37
Correlation r formula
r = 1/n-1 (x-mean of x/standard deviation of x) (y-mean of y/standard deviation of y)
38
Correlation r
Measures direction and strength. Between -1 and 1. Positive if positive correlation, negative if negative correlation
39
Regression line
A straight line that shows how the response variable changes as the explanatory variable changes. Used to predict the value of y for a given value of x.
40
Formula for predicting y (regression line)
y = slope (x) + intercept
41
Slope formula
Slope = r (standard deviation of y / standard deviation of x)
42
Slope
A change of one standard deviation in x corresponds to a change of r standard deviations in y
43
Measure of center and spread for symmetric data
Mean and standard deviation
44
Measure of center and spread for skewed data
Median and IQR