Question
In: Statistics and Probability
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 slope, beta1.
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
=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.
Two key concepts in hypothesis testing are the null and the alternative hypothesis. Formulating the hypothesis...
Two key concepts in hypothesis testing are the null
and the alternative hypothesis. Formulating the hypothesis test in
the right manner, i.e. by correctly formulating null and
alternative hypothesis is the first step towards solving the
problems in the right manner.
How do we represent these concepts tl (i.e. what abbreviation we
use to denote null and alternative hypothesis)?
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...
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...
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...
True or False A. In hypothesis testing, if you fail to reject the null hypothesis, then...
True or False
A. In hypothesis testing, if you fail to reject the null
hypothesis, then you have proven the null hypothesis to be
true.
B. If you are more concerned about a type I error than a type II
error in a hypothesis test, it would be better to use ∝= .01 than
∝= .10.
C. If you have complete information for a population (from a
census), it would be unnecessary and inappropriate to carry out a
hypothesis test...
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