
Concept explainers
For a linear equation y = b0 + b1x, identify the
- a. independent variable.
- b. dependent variable
- c. slope.
- d. y-intercept.
a.

To identify: The independent variable for a linear equation
Answer to Problem 1RP
The independent variable for a linear equation
Explanation of Solution
Given info:
The linear equation is
Justification:
In case of regression equation the independent variable is that variable whose variation is independent of other variables.
In the regression equation the predictor variable x is an independent variable.
b.

To identify: The dependent variable for a linear equation
Answer to Problem 1RP
The dependent variable for a linear equation
Explanation of Solution
Justification:
In case of regression equation the dependent variable is that response variable which responds to the independent variable.
In the regression equation the response variable y is an dependent variable.
c.

To identify: The slope for a linear equation
Answer to Problem 1RP
The slope for a linear equation
Explanation of Solution
Justification:
In case of regression equation the slope measure the change of dependent variable due to the unit change of independent variable.
In the regression equation, the slope is
d.

To identify: The y-intercept for a linear equation
Answer to Problem 1RP
The y-intercept for a linear equation
Explanation of Solution
Justification:
In case of regression equation the y-intercept implies that the y-value where the line intersect the y-axis.
In the regression equation, the y-intercept is
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Chapter 14 Solutions
Introductory Statistics (10th Edition)
- Please conduct a step by step of these statistical tests on separate sheets of Microsoft Excel. If the calculations in Microsoft Excel are incorrect, the null and alternative hypotheses, as well as the conclusions drawn from them, will be meaningless and will not receive any points 2. Two-Sample T-Test: Compare the average sales revenue of two different regions to determine if there is a significant difference. (Hints: The null can be about maintaining status-quo or no difference among groups; if alternative hypothesis is non-directional use the two-tailed p-value from excel file to make a decision about rejecting or not rejecting null) H0 = H1=arrow_forwardPlease conduct a step by step of these statistical tests on separate sheets of Microsoft Excel. If the calculations in Microsoft Excel are incorrect, the null and alternative hypotheses, as well as the conclusions drawn from them, will be meaningless and will not receive any points 3. Paired T-Test: A company implemented a training program to improve employee performance. To evaluate the effectiveness of the program, the company recorded the test scores of 25 employees before and after the training. Determine if the training program is effective in terms of scores of participants before and after the training. (Hints: The null can be about maintaining status-quo or no difference among groups; if alternative hypothesis is non-directional, use the two-tailed p-value from excel file to make a decision about rejecting or not rejecting the null) H0 = H1= Conclusion:arrow_forwardPlease conduct a step by step of these statistical tests on separate sheets of Microsoft Excel. If the calculations in Microsoft Excel are incorrect, the null and alternative hypotheses, as well as the conclusions drawn from them, will be meaningless and will not receive any points. The data for the following questions is provided in Microsoft Excel file on 4 separate sheets. Please conduct these statistical tests on separate sheets of Microsoft Excel. If the calculations in Microsoft Excel are incorrect, the null and alternative hypotheses, as well as the conclusions drawn from them, will be meaningless and will not receive any points. 1. One Sample T-Test: Determine whether the average satisfaction rating of customers for a product is significantly different from a hypothetical mean of 75. (Hints: The null can be about maintaining status-quo or no difference; If your alternative hypothesis is non-directional (e.g., μ≠75), you should use the two-tailed p-value from excel file to…arrow_forward
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- What is one sample T-test? Give an example of business application of this test? What is Two-Sample T-Test. Give an example of business application of this test? .What is paired T-test. Give an example of business application of this test? What is one way ANOVA test. Give an example of business application of this test? 1. One Sample T-Test: Determine whether the average satisfaction rating of customers for a product is significantly different from a hypothetical mean of 75. (Hints: The null can be about maintaining status-quo or no difference; If your alternative hypothesis is non-directional (e.g., μ≠75), you should use the two-tailed p-value from excel file to make a decision about rejecting or not rejecting null. If alternative is directional (e.g., μ < 75), you should use the lower-tailed p-value. For alternative hypothesis μ > 75, you should use the upper-tailed p-value.) H0 = H1= Conclusion: The p value from one sample t-test is _______. Since the two-tailed p-value…arrow_forward4. Dynamic regression (adapted from Q10.4 in Hyndman & Athanasopoulos) This exercise concerns aus_accommodation: the total quarterly takings from accommodation and the room occupancy level for hotels, motels, and guest houses in Australia, between January 1998 and June 2016. Total quarterly takings are in millions of Australian dollars. a. Perform inflation adjustment for Takings (using the CPI column), creating a new column in the tsibble called Adj Takings. b. For each state, fit a dynamic regression model of Adj Takings with seasonal dummy variables, a piecewise linear time trend with one knot at 2008 Q1, and ARIMA errors. c. What model was fitted for the state of Victoria? Does the time series exhibit constant seasonality? d. Check that the residuals of the model in c) look like white noise.arrow_forwardce- 216 Answer the following, using the figures and tables from the age versus bone loss data in 2010 Questions 2 and 12: a. For what ages is it reasonable to use the regression line to predict bone loss? b. Interpret the slope in the context of this wolf X problem. y min ball bas oft c. Using the data from the study, can you say that age causes bone loss? srls to sqota bri vo X 1931s aqsini-Y ST.0 0 Isups Iq nsalst ever tom vam noboslios tsb a ti segood insvla villemari aixs-Yediarrow_forward
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