Question
In: Statistics and Probability
provide two examples of 2 quantive variables that you msy have a linear relationship and estimate...
provide two examples of 2 quantive variables that you msy have a
linear relationship and estimate what tou think the value of the
correlation coefficient would be for two variables. Both variables
must be quantitative so the bakue of tge correlation coefficient
can be determinated
Solutions
orchestra answered 2 years agoRelated Solutions
You are testing the null hypothesis that there is no linear relationship between two variables, X...
You are testing the null hypothesis that there is no linear
relationship between two variables, X and Y. From your sample of n
equals 18, you determine that b1=4.2 and S Subscript b 1=1.1.
a. What is the value of t Subscript STAT?
b. At the alpha=0.05 level of significance, what are the
critical values?
c. Based on your answers to (a) and (b), what statistical
decision should you make?
d. Construct a 95% confidence interval estimate of the
population...
You are testing the null hypothesis that there is no linear relationship between two variables, X...
You are testing the null hypothesis that there is no linear
relationship between two variables, X and Y. From your sample of n
=18, you determine that b1=4.2 and Sb1equals=1.2
a. What is the value of tSTAT?
b. At the alphaα=0.05 level of significance, what are the
critical values?
c. Based on your answers to (a) and (b), what statistical
decision should you make?
d. Construct a 95% confidence interval estimate of the
population slope, betaβ1.
You are testing the null hypothesis that there is no linear relationship between two variables, X...
You are testing the null hypothesis that there is no linear
relationship between two variables, X and Y. From your sample of
n=18, you determine that b1=4.4 and Sb1=1.3
a. What is the value of t stat?
b. At the a=0.05 level of significance, what are the critical
values?
c. Based on your answers to (a) and (b), what statistical
decision should you make?
d. Construct a 95% confidence interval estimate of the
population slope,β1.
A measure of the strength of the linear relationship that exists between two variables is called:...
A measure of the strength of the linear relationship that exists
between two variables is called: Slope/Intercept/Correlation
coefficient/Regression equation. If both variables X and Y increase
simultaneously, then the coefficient of correlation will be:
Positive/Negative/Zero/One. If the points on the scatter diagram
indicate that as one variable increases the other variable tends to
decrease the value of r will be: Perfect positive/Perfect
negative/Negative/Zero. The range of correlation coefficient is: -1
to +1/0 to 1/-∞ to +∞/0 to ∞. Which of...
1. Select at least three variables that you believe have a linear relationship. a. Specify how...
1. Select at least three variables that you believe have a
linear relationship. a. Specify how you will measure each of these
variables (i.e., what instrument will you use and provide an APA
reference for the instrument
Select at least three variables that you believe have a linear relationship. Specify which variable is...
Select at least three variables that you believe have a linear
relationship.
Specify which variable is dependent and which are
independent.
Collect the data for these variables and describe your data
collection technique and why it was appropriate as well as why the
sample size was best.
Submit the data collected by submitting the SPSS data file with
your submission.
Find the Correlation coefficient for each of the possible
pairings of dependent and independent variables and describe the
relationship in...
Consider a possible linear relationship between two variables that you would like to explore Define the...
Consider a possible linear relationship between two variables
that you would like to explore
Define the relationship of interest and a data collection
technique.
Determine the appropriate sample size and collect the data.
Perform the appropriate analysis to determine if there is a
statistically significant linear relationship between the two
variables.
Describe the relationship in terms of strength and
direction.
Construct a model of the relationship and evaluate the validity
of that model.
1. The linear correlation coefficient r measures of the linear relationship between two variables. (a) Distance...
1. The linear correlation coefficient r measures of the linear
relationship between two variables. (a) Distance (b) size (c)
strength (d) direction 2. 10 pairs of sample data were obtained
from a study which looked at household income and the number of
people in the household who smoked (cigarettes). The value of the
linear correlation coefficient r was computed and a result of -
0.989 was obtained. All of the following (below) are conclusions
that can be drawn from the...
1. The linear correlation coefficient r measures of the linear relationship between two variables. (a) Distance...
1. The linear correlation coefficient r measures of the linear
relationship between two variables. (a) Distance (b) size (c)
strength (d) direction 2. 10 pairs of sample data were obtained
from a study which looked at household income and the number of
people in the household who smoked (cigarettes). The value of the
linear correlation coefficient r was computed and a result of -
0.989 was obtained. All of the following (below) are conclusions
that can be drawn from the...
1. The linear correlation coefficient r measures of the linear relationship between two variables. (a) Distance...
1. The linear correlation coefficient r measures of the linear
relationship between two variables. (a) Distance (b) size (c)
strength (d) direction 2. 10 pairs of sample data were obtained
from a study which looked at household income and the number of
people in the household who smoked (cigarettes). The value of the
linear correlation coefficient r was computed and a result of -
0.989 was obtained. All of the following (below) are conclusions
that can be drawn from the...
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