Identify a situation where using correlation coefficient is
appropriate. Could a regression equation be used in the same
situation? How are correlation and regression alike? How are they
different?
Find the equation of the least-squares regression line ŷ and the
linear correlation coefficient r for the given data. Round the
constants, a, b, and r, to the nearest hundredth.
{(0, 10.8), (3, 11.3), (5, 11.2), (−4, 10.7), (1, 9.3)}
Q1: Define the following terms:
a. correlation coefficient
b. scatter plot
c. bivariate relationship
Q2: Provide an example where the outlier is more important to the research than the other observations?
Q3: Identify when to use Spearman’s rho
Answer the questions below based on the following
table:
Fatigue
Vigor
Sleepiness
Tension
.36*
–.31*
.08
Fatigue
–.73***
.57**
Vigor
–.49**
* p < .05, **
p < .01, *** p < .001
The strongest correlation is between _________________________
and ________________________. (Give variable names)
The weakest correlation is between __________________________
and ________________________. (Give variable names)
The correlation between sleepiness and fatigue is
___________________
(indicate direction) and
________________________ (indicate strength).
1. When examining
the relation between two variables, when is it...
Show how; Independent t-test ,
Coefficient of determination, Exploratory factor analysis,
Chi-square test, Correlation
coefficient, R-squared value, Analysis of
covariance, Analysis of variance are applied in analysis of
quantitative data ( explain in simple English please)
A. Define the following terms:
-Correlation
-Causation
B. How do we know when 2 variables are correlated?
C. Explain the following: “Correlation does not equal
Causation”
D. What requirements must be met to satisfy Causation?
Question 1: If R squared=0.64 for the linear
regression equation Y= 3.2X+ 2.8 + error , Where Y (or response
variable) = stopping distance and X (or explanatory variable)=
Velocity which of the following are true?
a.) That 64 % of the variation in Stopping distance is
explained by velocity and the correlation coefficient R= -0.8
b.) That 64 % of the variation in Stopping distance is
explained by velocity and the correlation coefficient R= 0.8
c.) That velocity (X)...
Define the following terms. Give an example of the relevance of
the term in an industrial setting. i.Boiling Point:
ii. Vapor Pressure:
iii. Lower Explosive Limit:
iv. Upper Explosive Limit:
v. Rate of Evaporation: