15.3.9: Chapter 10 Lab
- Page ID
- 28623
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)One Population Hypothesis Testing
Year | Year of Sale |
Price | Sale price in $Thousands |
Bedrooms | Number of bedrooms |
SqrFeet | Size of home in 100's of square feet |
Pool | Does a home have a pool ? (Yes/No) |
Garage | Does a home have a garage? (Yes/No) |
Bath | Number of Bathrooms |
Distance | Distance in miles from city center |
City | City Region (Fresno, Los Angeles, Sacramento, San Francisco, San Jose) |
School | School District Rating (Poor, Fair, Good , Excellent) |
- You want to conduct a hypothesis test about the mean home prices in California using the housing data file: housing.mpj. At the 1% significance level, design the test for the hypothesis that the mean housing price is over $850,000.
- First create a dotplot for the price data, and paste the results here. Does the value $850,000 seem to be at the center of the data, above the center of the data, or below the center of the data?
- State the null and alternative hypotheses in words.
- State the null and alternative hypotheses in population parameters.
- What model are you choosing and what assumptions are needed? Do you think the skewness and high outlier are a problem in choosing this model?
- Conduct the test at a significance level of 1%, using MINITAB command Stat>Basic Statistics>1 Population \(t\)‐test. Make sure you choose options to set \(H_a\). Paste the results here. All price data is in $thousands, so you would enter $850,000 as 850.
- Do you reject or fail to reject \(H_o\)?
- State your conclusion in the context of the problem.
- Using the online or Minitab power calculator, determine the power of the test if the population mean is really $900,000. Assume the standard deviation is $450,000. (Remember the data is entered in $ thousands).
- Using the online or Minitab power calculator, determine the sample size needed to have 95% power for the test.
- You want to conduct a hypothesis test about the standard deviation of home prices in California using the housing data file: housing.mpj. At the 5% significance level, design a test to support the claim that the standard deviation housing price is not $400,000.
- State the null and alternative hypotheses in words.
- State the null and alternative hypotheses in population parameters.
- What model are you choosing and what assumptions are needed?
- Conduct the test at a significance level of 5%, using MINITAB command Stat>Basic Statistics>1 Variance. Make sure you choose options to set \(H_a\). Paste the results here.
- Do you reject or fail to reject \(H_o\)?
- State your conclusion in the context of the problem.
- For the housing data above, we want to support the claim that the percentage of homes in California with garages is over 60%. We are going to conduct a Hypothesis Test using a significance level of 10%.
- State the null and alternative hypotheses in words.
- State the null and alternative hypotheses in population parameters.
- Create a bar chart of garages and under Chart Option, click the box to show \(y\) as a percentage. Does the bar graph support the claim that more than 60% of homes have garages?
- What model are you choosing and what assumptions are needed?
- Using the online power calculator, determine the power of the test if the population proportion under \(H_a\) is 0.65
- Conduct the test at a significance level of 5%, using MINITAB command Stat>Basic Statistics>1 Proportion. Make sure you choose options to set \(H_a\). Paste the results here.
- Do you reject or fail to reject \(H_o\)?
- State your conclusion in the context of the problem.