Intro Stats
4th Edition
ISBN: 9780321826275
Author: Richard D. De Veaux
Publisher: PEARSON
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Chapter 23, Problem 22E
a.
To determine
Explain in context about the regression says.
b.
To determine
Discuss the value of the intercept by taking note of its P-value.
c.
To determine
Explain the meaning of the output
d.
To determine
Find the value of the standard error of the slope of the regression line.
e.
To determine
Explain the meaning of the standard error in the context.
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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…
4. 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.
ce-
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
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c. Using the data from the study, can you
say that age causes bone loss?
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Chapter 23 Solutions
Intro Stats
Ch. 23.4 - Researchers in Food Science studied how big...Ch. 23.4 - Prob. 2JCCh. 23.4 - Prob. 3JCCh. 23 - Prob. 1ECh. 23 - Prob. 2ECh. 23 - Prob. 3ECh. 23 - Prob. 4ECh. 23 - Prob. 5ECh. 23 - Prob. 6ECh. 23 - Prob. 7E
Ch. 23 - Prob. 8ECh. 23 - Prob. 9ECh. 23 - Prob. 10ECh. 23 - Prob. 11ECh. 23 - 12. Shoot to score, double overtime One of the...Ch. 23 - Prob. 13ECh. 23 - Prob. 14ECh. 23 - Prob. 15ECh. 23 - Prob. 16ECh. 23 - Prob. 17ECh. 23 - Prob. 18ECh. 23 - Prob. 19ECh. 23 - Prob. 20ECh. 23 - Prob. 21ECh. 23 - Prob. 22ECh. 23 - Prob. 23ECh. 23 - Prob. 24ECh. 23 - Prob. 25ECh. 23 - Prob. 26ECh. 23 - Prob. 27ECh. 23 - Prob. 28ECh. 23 - Prob. 29ECh. 23 - Prob. 30ECh. 23 - Prob. 31ECh. 23 - Prob. 32ECh. 23 - Prob. 33ECh. 23 - Prob. 34ECh. 23 - Fuel economy A consumer organization has reported...Ch. 23 - 36. SAT scores How strong was the association...Ch. 23 - Prob. 37ECh. 23 - 38. SATs, part II Consider the high school SAT...Ch. 23 - 39. Fuel economy, part III Consider again the data...Ch. 23 - 40. SATs, again Consider the high school SAT...Ch. 23 - Cereals A healthy cereal should be low in both...Ch. 23 - Brain size Does your IQ depend on the size of your...Ch. 23 - Prob. 43ECh. 23 - Prob. 44ECh. 23 - Prob. 45ECh. 23 - Prob. 46ECh. 23 - Ozone and population The Environmental Protection...Ch. 23 - Prob. 48ECh. 23 - Prob. 49ECh. 23 - 50. More sales and profits Consider again the...Ch. 23 - Prob. 51ECh. 23 - Crawling Researchers at the University of Denver...Ch. 23 - 53. Body fat Do the data shown in the table below...Ch. 23 - Prob. 54ECh. 23 - Midterms The data set below shows midterm and...Ch. 23 - Prob. 56ECh. 23 - Prob. 57ECh. 23 - All the efficiency money can buy 2011 A sample of...Ch. 23 - Education and mortality The following software...Ch. 23 - Property assessments The following software output...Ch. 23 - Prob. 61ECh. 23 - Prob. 62E
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- 120 110 110 100 90 80 Total Score Scatterplot of Total Score vs. Putts grit bas 70- 20 25 30 35 40 45 50 Puttsarrow_forward10 15 Answer the following, using the figures and tables from the temperature versus coffee sales data from Questions 1 and 11: a. How many coffees should the manager prepare to make if the temperature is 32°F? b. As the temperature drops, how much more coffee will consumers purchase?ov (Hint: Use the slope.) 21 bru sug c. For what temperature values does the voy marw regression line make the best predictions? al X al 1090391-Yrit,vewolf 30-X Inlog arts bauoxs 268 PART 4 Statistical Studies and the Hunt forarrow_forward18 Using the results from the rainfall versus corn production data in Question 14, answer DOV 15 the following: a. Find and interpret the slope in the con- text of this problem. 79 b. Find the Y-intercept in the context of this problem. alb to sig c. Can the Y-intercept be interpreted here? (.ob or grinisiques xs as 101 gniwollol edt 958 orb sz) asiques sich ed: flow wo PEMAIarrow_forward
- Variable Total score (Y) Putts hit (X) Mean. 93.900 35.780 Standard Deviation 7.717 4.554 Correlation 0.896arrow_forward17 Referring to the figures and tables from the golf data in Questions 3 and 13, what hap- pens as you keep increasing X? Does Y increase forever? Explain. comis word ே om zol 6 svari woy wol visy alto su and vibed si s'ablow it bas akiog vino b tad) beil Bopara Aon csu How wod griz -do 30 義arrow_forwardVariable Temperature (X) Coffees sold (Y) Mean 35.08 29,913 Standard Deviation 16.29 12,174 Correlation -0.741arrow_forward
- 13 A golf analyst measures the total score and number of putts hit for 100 rounds of golf an amateur plays; you can see the summary of statistics in the following table. (See the figure in Question 3 for a scatterplot of this data.)noitoloqpics bella a. Is it reasonable to use a line to fit this data? Explain. 101 250 b. Find the equation of the best fitting 15er regression line. ad aufstuess som 'moob Y lo esulav in X ni ognado a tad Variable on Mean Standard Correlation 92 Deviation Total score (Y) 93.900 7.717 0.896 Putts hit (X) 35.780 4.554 totenololbenq axlam riso voy X to asulisy datdw gribol anil er 08,080.0 zl noitsism.A How atharrow_forwardVariable Bone loss (Y) Age (X) Mean 35.008. 67.992 Standard Deviation 7.684 10.673 Correlation 0.574arrow_forward50 Bone Loss 30 40 20 Scatterplot of Bone Loss vs. Age . [902) 10 50 60 70 80 90 Age a sub adi u xinq (20) E 4 adw I- nyd med ivia .0 What does a scatterplot that shows no linear relationship between X and Y look like?arrow_forward
- Variable Temperature (X) Coffees sold (Y) Mean 35.08 29,913 Standard Deviation 16.29 12,174 Correlation -0.741arrow_forward2 Find and interpret the value of r² for the rainfall versus corn data, using the table from Question 14.2291992 b sgen gnome vixists 992 ms up? 2910 1999 bio .blos estos $22 tolqis2 qs rieds ni zoti swoH iisqa vilsen od 1'meo DOV to mogers boangas mus jil Reustar enou Leption20th ) abnuin Hagodt graub 032 Carrow_forward18 Using the results from the rainfall versus corn production data in Question 14, answer oy the following: DOY 98 103 LA Find and interpret the slope in the con- text of this problem. b. Find the Y-intercept in the context of this problem. roy gatiigisve Toy c. Can the Y-intercept be interpreted here? (.ob o grinisq blo eiqmaxs as 101 galwollol edt 998 ds most notamotni er griau sib 952) siqmaxs steb godt llaw worl pun MAarrow_forward
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