Department

Sociology

Course Code

SOC202H1

Professor

Brent Berry

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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