2:Descriptive Stats Reslationships Between Varibles Part 2 Flashcards

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1
Q

Pearson r

A

Two quantitative variables
Correlation coefficient
-linear relationship between 2 QUAN variables (interval or ratio) normal
Sign of r tells u direction of relations between variables
Magnitude of r absolute value tells u the strength of linear relationship between variables

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2
Q

Cohens d

A

One dichotomous categorical and one quantitative to compare means of two distributions

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3
Q

Scatterplot

A

X= IV
Y= DV
Display paired data from a set of individual cases
-may include best fit

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4
Q

Positive correlation

A

Increase in one is increase in other. Positive slope

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5
Q

Negative correlation

A

Increase in one variable accompanies a decrease in other. Negative slope.

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6
Q

Magnitude of r

A

The larger the magnitude of r, the closer the data points are to the best-fit straight line.

Coefficient determination: r^2 percentage of variation in B explained by A

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7
Q

Side by side box plots

A

Comparing means. Data from multiple

Groups or conditions compared side by side.

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8
Q

Bar graphs

A

Comparing means.
Display means as bars extending from categorical axis
-heigh/length of each represents mean value of quantity variable for cases at that value of categorical variable
-error bars illustrate variability as whiskers extending from top of bar
EMPHASIZE DIFFERENCES BETWEEN MEANS

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9
Q

Factorial designs

A

One categorical variable along the categorical axis (X)

-other categorical variable in legend

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10
Q

Line graphs

A

Comparing means
Means as points connected by line segments
-x is ordinal scale or higher
-if x variable is quantitative but discrete, the x axis is scaled with units (distance is meaningful)
-EMPHASIZE CHANGES IN MEAN VALUE OF Y AS FUNCTION OF X

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11
Q

Functional relationships

A

Characterized based on how the value of Y changes as the X increases
Monotonic: continuously increasing or decreasing
Nonmonotonic: contains at least one reversal in direction
Asymptotic: if curve levels off

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12
Q

Cohens d effect size

A

Difference in means relative to pooled standard deviation of 2 distributions
-less overlap of distributions = larger cohens d = larger effect size
(Stronger relationship or association)

M1-M2/ SD

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13
Q

If both variables categorical

A

Must display counts or proportions for number of cases at each combo

  • frequency table
  • multicolor or patterned histogram with two or more series
  • side by side pie graphs
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