Stats

Front 1

slope interpretation:
b=-.289

Back 1

everytime the rate of x increases by 1 then y decreases by .2893

everytime the rate of violent crime increases by 1 the number of additional officers hired decreases by .289

Front 2

interpret the predicted value when x=100

Back 2

when x=100 then y is predicted to be 13.

when the rate of violence is 100/10,000, the number of additional officers hired is predicted to be 13.

Front 3

interpret Pearson's r
when r=-.8
when r=88

Back 3

the relationship between x and y is negative and negative and strong

the relationship between x and y is positive and strong

the relationship between the rate of violent crimes and the number of additional police officers hired is negative and strong

Front 4

interpret variance
r2=.66

Back 4

66% of the variance of y is associated with x
66% of the variance of the number of additional police officers hired is associated with the rates of violent crime.

Front 5

tobt interpretation
when tobt=-4.627
and tcrit=-1.796

Back 5

For a one tailed hypothesis test with an alpha of .05, we reject the null and we are 95% certain that in the population, there is a statistically significant negative relationship between the rate of violent crime and the number of additional police officers hired.

Front 6

multi variation regression
y-int interpretation
y=2.8

Back 6

when x1 and x2 are both 0 then expected y is 2.8
If person consumes 0 drinks with a score of 0 on the BMI then the expected inebriation score would be 2.8.

Front 7

Beta weights
when beta weight x1=1 and beta weight x2=-.9

Back 7

It determines which indep variable contributes most to dependent variable

1>-.9 (or 1>.9) so x1-# of drinks contributes slightly more than x2, BMI score to predicting y, inebritation scores.

Front 8

p value

Back 8

.05 alpha means 5% chance null hyp is true
p=.01 means 1% chance null hyp is true.