Department

SociologyCourse Code

SOC202H1Professor

Brent BerryChapter

14This

**preview**shows half of the first page. to view the full**3 pages of the document.**Chapter 14

The key element of statistical imagination is the analysis if cause and consequences

with the goal to predicting future events

The test estimate of a dependent variable can be imposed if we can identify

independent variable and extend the analysis to the bivariate level

Correlation: is a systematic change in the scores of 2 interval ration variable (when

the change in one variable change in tandem with the measurement of the other)

2 variable correlated if their measurement consistently change together form case to

case

Simple bivariate linear correlation and regression analysis

1)Procedure of improving best estimate of Y by accounting for its relationship with

X (main goal to reduce error in prediction)

2)Central idea: use a straight line to improve best estimate of an interval ratio (y)

for all values of interval ration (x)

3)The formula to estimate Y Y’= a+bX (applies only when both variable are

interval ration- used only with linear relationship between X and Y

Scartterplot: a two-dimensional grid of the coordinate of two interval-ration

variables X and Y

Coordinate: a point on a scatterplot where the values of X and Y are plotted for a

case

Linear patterns: on where the coordinate of the scatterplot fall into a shape of a

straight line

The horizontal axis provided values of a variable X (x axis) and the vertical axis

represents value of the second interval variable Y (y axis)

X-> the predicator (independent) y-> the dependent variable

When 2 variables increase in tandem it is called a positive relationship/ when x

increases and y decreases it is a negative correlation

When no correlation exist between x and y, the mean of Y remains the best estimate

of Y for all values of X

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