Statistics Test 4 Flashcards
What is the independent effect?
it is when the original relationship is not affected by a second independent variable
What is the explanation effect?
It is when the original relationship is spurious the second independent variable cause y
Determinism:
absence of randomness outcomes are caused by something
Rule of P
to be significant or reject Ho p must be less than .05
to be not significant or accept Ho p must be greater or equal to .05
When you use correlation coefficient attach:
scattergram
Locate outliers,
raise the question and speculate
Define type 1 error:
to reject the null hypothesis when its true
Define type 2 error:
to accept the null hypothesis when its false
The greater the dimension,
the higher the code
In a scattergram what goes on a horizontal line is the,
independent variable
In a scattergram what goes on a vertical line is the,
dependent variable
When you are a manager:
never trust a biserial/biveriate relationship; truism
The best predictor of the future(y) is the:
past(x). The past is the single best predictor
Why does scatter matter?
bc management aim of correlation is to predict (y)
The relationship between scatter and prediction:
the more the scatter the less the prediction
the less the scatter the better the prediction
What is correlation coefficient?
it is one number that summarizes a scattergram
You interpret the direction by the _______ and you interpret the strength by the _______.
Sign & scatter
What do you miss in a correlation coefficient?
outliers
Correlation coefficient is an inferential tool?
False
William S. Gasset:
Created student T
If alpha equals .05 in a sample of N=10 in a two tail test, t is
+ or - 2.306
Biveriate analysis,
one independent variable, one dependent variable. The independent variable in the caption, and the dependent variable in the stub
Multivariate analysis,
Two independent variable, one dependent variables. The two independent variable are in the caption
Beta:
measures the relationship between X and Y
Singular linear regression:
y = a + b(x)
x is the independent variable
y is the dependent variable
b is the beta
Multiple linear regression:
y = a + b(x) + b(x)
It is important for managers:
to raise the question
alpha synonyms
level f signifcance
lower case p
sig
