Question 1

Change the exponential expression to an equivalent expression involving a logarithm.
-$\log _ { 5 } 125 = x$

Accepted Answer

A)  $5 ^ { x } = 125$ 
B)  $x ^ { 5 } = 125$ 
C)  $125 x = 5$ 
D)  $125 ^ { 5 } = x$ 
A)  $5 ^ { x } = 125$ 
B)  $x ^ { 5 } = 125$ 
C)  $125 x = 5$ 
D)  $125 ^ { 5 } = x$

Question 2

Find the Least-Squares Regression Line and Use the Line to Make Predictions
-The data below are the average one-way commute times (in minutes) for selected students and the number of absences for those students during the term. Find the equation of the regression line for the given data. What would be the predicted number of absences if the commute time was 40 minutes? Is this a reasonable question? Round the predicted number of absences to the nearest whole number.

Accepted Answer

A)  $\hat  { y } = 0.449 \mathrm { x } - 30.27 ; - 12$ absences; No, it is not reasonable. 40 minutes is well outside the scope of the model.
  
B)  $\hat  { y } = 0.449 \mathrm { x } - 30.27 ; - 12$ absences; $\mathrm { Yes }$, it is reasonable. 
C)  $\hat { y } = 0.449 \mathrm { x } + 30.27 ; 48$ absences; Yes, it is reasonable. 
D)  $\hat  { y } = 0.449 \mathrm { x } + 30.27 ; 48$ absences; No, it is not reasonable. 40 minutes is well outside the scope of the model. 
A)  $\hat  { y } = 0.449 \mathrm { x } - 30.27 ; - 12$ absences; No, it is not reasonable. 40 minutes is well outside the scope of the model.
  
B)  $\hat  { y } = 0.449 \mathrm { x } - 30.27 ; - 12$ absences; $\mathrm { Yes }$, it is reasonable. 
C)  $\hat { y } = 0.449 \mathrm { x } + 30.27 ; 48$ absences; Yes, it is reasonable. 
D)  $\hat  { y } = 0.449 \mathrm { x } + 30.27 ; 48$ absences; No, it is not reasonable. 40 minutes is well outside the scope of the model.

Question 3

Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists.
-$\begin{array}{c|ccccc}
\mathrm{x} & 2 & 3 & 5 & 5 & 6 \
\hline \mathrm{y} & 1.3 & 1.6 & 2.1 & 2.2 & 2.7
\end{array}$

Accepted Answer

A)  $r = 0.983$; linear relation exists 
B)  $r = 0.983$; no linear relation exists 
C)  $\mathrm { r } = 0.883$; linear relation exists 
D)  $\mathrm { r } = 0.883$; no linear relation exists 
A)  $r = 0.983$; linear relation exists 
B)  $r = 0.983$; no linear relation exists 
C)  $\mathrm { r } = 0.883$; linear relation exists 
D)  $\mathrm { r } = 0.883$; no linear relation exists

Change the exponential expression to an equivalent expression involving a logarithm. - $\log _ { 5 } 125 = x$

Compute the linear correlation coefficient between the two variables and determine whether a linear relation exists. - 2 3 5 5 6 1.3 1.6 2.1 2.2 2.7

Data Collection

Creating Tables and Drawing Pictures of Data

Numerically Summarizing Data

Probability

Discrete Probability Distributions

The Normal Probability Distribution

Sampling Distributions

Estimating the Value of a Parameter Using Confidence Intervals

Hypothesis Tests Regarding a Parameter

Inference on Two Samples

Inference on Categorical Data

Comparing Three or More Means

Inference of the Least-Squares Regression Model and Multiple Regression

Nonparametric Statistics

Filters

Exam 4: Describing the Relation Between Two Variables

Change the exponential expression to an equivalent expression involving a logarithm. - log⁡5125=x\log _ { 5 } 125 = xlog5​125=x