## STAT 30100: Elementary Statistical Methods I

STAT 30100: Elementary Statistical Methods IDepartment of Mathematical SciencesSchool of Science, IUPUIProject # 3FALL 2015, Total 25 pointsDue Date:11/18/2015Name:________________________________________________________Important Instructions:You must work independently to answer all questions. Provide complete and clear explanations to all questions.Graphs must be labeled for clear communication. (Remember the importance of context throughout!) Yourproject must be typed, easy to read and have the answer to each question identified by question number. Copy andpaste the specified StatCrunch output, including graphs and number summaries, into the specified table. Theindicated StatCrunch output MUST appear with the discussion, not as separate pages. Also, consider at leastthree decimals for your calculation throughout the project.Problem # 1The manager of a local soft-drink bottling company believes that when a new beverage-dispensing machine is setto dispense 7 ounces, it in fact dispenses an amount x at random anywhere between 6.5 and 7.5 ounces, inclusive.Suppose x has a uniform probability distribution.Now we will explore the following questions or ideas.(a)Using calculator, find the mean and standard deviation of the variable x.[Â½ + Â½ = 1 pt]==(b)Generate 5000 samples of 50 observations each from the uniform distribution.NO RESULTS TO BE REPORTED.[ StatCrunch: Data -> Simulate data -> Uniform (Rows: 5000, Columns: 50, Uniform parametersa: 6.5, b: 7.5) -> Simulate ]Note that each row indicates a sample consisting of 50 data values.(c)Calculate the 5000 sample means. NO RESULTS TO BE REPORTED[ StatCrunch: Stat-> Summary Stats ->Rows (select all variables from left to right)Select nextKeep only mean on the right side of the box by clicking each on the leftside except meanCheck mark at âStore output in data tableâCalculateYou will see a new column has been added named âRow Meanâ in the dataset. This Rowmean is the mean of each sample.(d)By the Central Limit Theorem, we know the variable âRow Meanâ has an approximate Normaldistribution.(i)What are the parameter values?[Â½ + Â½ = 1 pt][ StatCrunch: Go to Stat -> Summary Stats -> Column (select Row Mean) -> CalculateReport mean and standard deviation only ]x Row Meanx Row Mean(ii)nDraw a histogram of âRow Meanâ with the appropriate Normal PDF overlaid. Does thisgraph look as you would have expected?[Â½ + Â½ = 1 pt][ StatCrunch: GO TO Graphics -> Histogram -> Choose the variable Row Mean -> Next ->Next-> Choose Overlay density Normal -> NextX axis label: Means of 5000 samplesY axis label: FrequencyTitle: Histogram of Normal Distribution Exploration by the CLT ]Click on Create Graph.(e)Now pretend that μ is unknown, but is still known. Calculate the margin of error(ME)σÂ± z α /2√n ) for a 95% confidence interval for μ based on a sample of size n = 50.Â¿[1 pt](f)Imagine calculating a 95% CI for μ using each of the 5000 samples. Of the 5000 CIs, how manywould you expect to contain the true value of μ? Explain.[ Â½ pt](g)Calculate the lower and upper limits of the 95% CIs. NO RESULTS TO BE REPORTED[ StatCrunch: GO TO Data->Compute expression -> âRow Meanâ-ME[ Â½ pt]GIVE New column name: lowerSIMILARLY DO âRow Meanâ+MEGIVE New column name: upper ](h)How many of the 5000 CIs covered μ? Is this consistent with your expectations in part (f)?[Â½ + Â½ = 1 pt][ StatCrunch: GO TO Data -> Compute expressionTYPE: between( , lower, upper)NOTE the value of comes from part (a)GIVE new column name: tallycountAgain, GO TO Data -> Compute expressionifelse(tallycount="true", 1,0)GIVE new column name: tallycount1GO TO Stat -> Tables-> Frequency (select variable tallycount1) and see thepercentage for 1 ]Problem # 2Studies were conducted in Los Angeles to determine the carbon monoxide (CO) concentration nearfreeways. The basic technique used was to capture air samples in special bags and to then determine thecarbon monoxide concentration by using a spectrophotometer. The measurements in ppm (parts permillion) over a sampled period during the year can be found in the Excel file CARBON.xlsx viaOncourse. Find a 90% confidence interval for Âµ, the mean CO concentration (in ppm) during the year.Consider the following steps for your answer.[1 pt](i)Label the parameter.(ii)Verify all required conditions. (using StatCrunc, produce a boxplot to verify the normalitycondition)[3 pts](iii)Interval calculations. (Both StatCrunch output and manual calculation must be reported; notethat answer should be same in both cases)[2+2 = 4 pts]StatCrunch output:Manual calculation:(iv)Interpret your result in part (iii) in the context of the problem.[1 pt]Problem # 3In a number of previous Phase I and II studies of male, non-insulin-dependent diabetic (NIDDM)patients conducted by Mylitech Biosystems, Inc., the mean body mass index (BMI) was found to be28.4. An investigator has 16 male NIDDM patients enrolled in a new study and wants to know if theBMI from this sample is consistent with previous findings. BMI is computed as the ratio of weight inkilograms to the square of the height in meters. The Excel data file BMI.xlsx shows the BMI for 16males. Conduct a hypothesis test at 5% level of significance to answer the question.Consider the following steps for your hypotheses test.(i)Formulate the hypotheses. (Level the parameter, null hypothesis, alternative hypothesis)(ii)Test statistic. (Name of the test you are going to use and verify all required conditions for your testusing the data; using StatCrunch, produce a boxplot to verify the normality condition)[3 pts.](iii)Calculation of your proposed test statistic and p-value. (Both StatCrunch output and manualcalculation must be reported; note that answer should be same in both cases)[3 pts.]StatCrunch output:Manual calculation:[2 pts.](iv)Decision and conclusion in the context.[2 pts.]

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