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What is the schedule for this project?

Strategic Planning for Public Relations

Please provide the following information for Problems $11-22$. (a) What is the level of significance? State the null and alternate hypotheses. (b) Check Requirements What sampling distribution will you use? Explain the rationale for your choice of sampling distribution. Compute the appropriate sampling distribution value of the sample test statistic. (c) Find (or estimate) the $P$ -value. Sketch the sampling distribution and show the area corresponding to the $P$ -value. (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level $\alpha ?$ (e) Interpret your conclusion in the context of the application. Note: For degrees of freedom $d . f .$ not given in the Student's $t$ table, use the closest $d . f .$ that is smaller. In some situations, this choice of $d . f .$ may increase the $P$ -value by a small amount and therefore produce a slightly more "conservative" answer. Medical: Hemoglobin Count Let $x$ be a random variable that represents hemoglobin count (HC) in grams per 100 milliliters of whole blood. Then $x$ has a distribution that is approximately normal, with population mean of about 14 for healthy adult women (see reference in Problem 17). Suppose that a female patient has taken 10 laboratory blood tests during the past year. The HC data sent to the patient's doctor are $\begin{array}{llllllllll}15 & 18 & 16 & 19 & 14 & 12 & 14 & 17 & 15 & 11\end{array}$ i. Use a calculator with sample mean and sample standard deviation keys to verify that $\bar{x}=15.1$ and $s \approx 2.51$. ii. Does this information indicate that the population average HC for this patient is higher than $14 ?$ Use $\alpha=0.01$.

Please provide the following information for Problems $11-22$. (a) What is the level of significance? State the null and alternate hypotheses. (b) Check Requirements What sampling distribution will you use? Explain the rationale for your choice of sampling distribution. Compute the appropriate sampling distribution value of the sample test statistic. (c) Find (or estimate) the $P$ -value. Sketch the sampling distribution and show the area corresponding to the $P$ -value. (d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level $\alpha ?$ (e) Interpret your conclusion in the context of the application. Note: For degrees of freedom $d . f .$ not given in the Student's $t$ table, use the closest $d . f .$ that is smaller. In some situations, this choice of $d . f .$ may increase the $P$ -value by a small amount and therefore produce a slightly more "conservative" answer. Medical: Hemoglobin Count Let $x$ be a random variable that represents hemoglobin count (HC) in grams per 100 milliliters of whole blood. Then $x$ has a distribution that is approximately normal, with population mean of about 14 for healthy adult women (see reference in Problem 17). Suppose that a female patient has taken 10 laboratory blood tests during the past year. The HC data sent to the patient's doctor are $\begin{array}{llllllllll}15 & 18 & 16 & 19 & 14 & 12 & 14 & 17 & 15 & 11\end{array}$ i. Use a calculator with sample mean and sample standard deviation keys to verify that $\bar{x}=15.1$ and $s \approx 2.51$. ii. Does this information indicate that the population average HC for this patient is higher than $14 ?$ Use $\alpha=0.01$.

Understandable Statistics Concepts and Methods

Hypothesis Testing

Testing the Mean $\mu$
Manufacturing time The assembly time in minutes for a component at an electronic manufacturing plant is normally distributed with a mean of $\mu=55$ and standard deviation $\sigma=4 .$ What is the probability that a component will be made in less than one hour?

Manufacturing time The assembly time in minutes for a component at an electronic manufacturing plant is normally distributed with a mean of $\mu=55$ and standard deviation $\sigma=4 .$ What is the probability that a component will be made in less than one hour?

Thomas Calculus

Techniques of Integration

Probability

Cost of Personal Computers The average price of a personal computer $(\mathrm{PC})$ is $\$ 949 .$ If the computer prices are approximately normally distributed and $\sigma=\$ 100$, what is the probability that a randomly selected $\mathrm{PC}$ costs more than $\$ 1200 ?$ The least expensive $10 \%$ of personal computers cost less than what amount?

Elementary Statistics a Step by Step Approach

The Normal Distribution

Applications of the Normal Distribution

Questions asked

ANSWERED

Ivan Kochetkov verified

Numerade educator

A dummy variable is used as an independent variable in a regression model when Group of answer choices the variable involved is categorical. a curvilinear relationship is suspected. 2 independent variables interact. the variable involved is numerical.

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ANSWERED

Ivan Kochetkov verified

Numerade educator

In a multiple regression problem involving two independent variables, if b1 is computed to be +2.0, it means that Group of answer choices the relationship between X1 and Y is significant. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, holding X2 constant. the estimated mean of Y increases by 2 units for each increase of 1 unit of X1, without regard to X2. the estimated mean of Y is 2 when X1 equals zero.

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INSTANT ANSWER

The Principal of an elementary school wanted to predict the percentage of students who would pass a sixth-grade proficiency test. She believes that the passing rate is related to the average teacher salary (in thousands of dollars) and instructional spending per pupil (in thousands of dollars). She collects data on 47 schools throughout the state, enters the data into Excel, and runs a multiple regression analysis. Following are the partial tables: SUMMARY OUTPUT Regression Statistics Multiple R 0.4276 R Square 0.1828 Adjusted R Square 0.1457 Standard Error 5.7351 Observations 47 Coeff Std Error T Stat P-value Intercept -72.9916 45.9106 -1.5899 0.1190 Salary 2.7939 0.8974 3.1133 0.0032 Spending 0.3742 0.9782 0.3825 0.7039 Which of the following is a correct statement? Group of answer choices 18.28% of the total variation in the percentage of students passing the proficiency test can be explained by instructional spending per pupil holding constant the effect of mean teacher salary. 18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary and instructional spending per pupil after adjusting for the number of predictors and sample size. 18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary and instructional spending per pupil. 18.28% of the total variation in the percentage of students passing the proficiency test can be explained by mean teacher salary holding constant the effect of instructional spending per pupil.

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ANSWERED

Ivan Kochetkov verified

Numerade educator

The coefficient of multiple determination (r) superscript (2) subscript (Y1.2) Group of answer choices measures the variation around the predicted regression equation. will have the same sign as b1. measures the proportion of variation in Y that is explained by X1 and X2. measures the proportion of variation in Y that is explained by X1 holding X2 constant.

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ANSWERED

Ivan Kochetkov verified

Numerade educator

True or False: A multiple regression is called "multiple" because it has several explanatory variables. Group of answer choices True False

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ANSWERED

Sanchit Jain verified

Numerade educator

Is there a relationship between demand for building materials (in hundreds of dollars per capita) and 2 variables: mortgage rate (in percent) and location (Los Angeles = 0 and San Francisco = 1)? A researcher thinks so, and believes that the appropriate model is Demand = 10 + 5 * Mortgage rate + 8 * location The predicted demand in Los Angeles when the mortgage rate is 8% is ________.

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ANSWERED

Robin Corrigan verified

Numerade educator

A real estate builder wishes to determine if family income (in thousands of dollars) and family size can help predict the size of house (in hundreds of square feet) a person buys. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: SUMMARY OUTPUT Regression Statistics egin{tabular}{|l|l|} hline Multiple R & 0.8479 \ hline R Square & 0.7189 \ hline Adjusted R Square & 0.7069 \ hline Standard Error & 0.299 \ hline Observations & 50 \ hline end{tabular} egin{tabular}{|l|l|l|c|c|} hline & multicolumn{1}{|c|}{ Coeff } & multicolumn{1}{c|}{ Std Error } & T Stat & P-value \ hline Intercept & -5.5146 & 7.2273 & -0.7630 & 0.4493 \ hline Income & 0.4262 & 0.0392 & 10.8668 & 0.0000 \ hline Family Size & 5.5437 & 1.6949 & 3.2708 & 0.0020 \ hline end{tabular} What is the predicted house size (in hundreds of square feet) for an individual with a family size of 2 and an income of ( $ 100,000 ) ?

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ANSWERED

Sanchit Jain verified

Numerade educator

The Dean at Cool State San Bernardino wants to see if he could predict the GPA of students using the number of course units and total SAT scores. He takes a sample of students and generates the following Microsoft Excel output: SUMMARY OUTPUT Regression Statistics egin{tabular}{|l|l|} hline Multiple R & 0.916 \ hline R Square & 0.839 \ hline Adjusted R Square & 0.732 \ hline Standard Error & 0.24685 \ hline Observations & 6 \ hline end{tabular} egin{tabular}{|l|c|l|c|c|} hline & Coeff & multicolumn{1}{|c|}{ Std Error } & T Stat & P-value \ hline Intercept & 4.5939 & 1.1337 & 4.052 & 0.0271 \ hline Units & -0.2473 & 0.0627 & -3.945 & 0.0290 \ hline Total SAT & 0.0014 & 0.0010 & 1.425 & 0.2494 \ hline end{tabular} The estimate of the change in the mean of GPA per unit change in the number of course units, holding SAT score constant, is

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ANSWERED

Sanchit Jain verified

Numerade educator

Last summer you had a job at the Barbie Insurance Company. You noticed that people's car insurance premiums depend on the person's age and the number of traffic tickets received over the previous 5 years. You collected some data and performed a regression analysis in EXCEL: SUMMARY OUTPUT Regression Statistics egin{tabular}{|l|l|} hline Multiple R & 0.8546 \ hline R Square & 0.7303 \ hline Adjusted R Square & 0.6853 \ hline Standard Error & 226.7502 \ hline Observations & 15 \ hline end{tabular} egin{tabular}{|l|l|c|c|c|} hline & Coeff & Std Error & T Stat & P-value \ hline Intercept & 821.2617 & 161.9391 & 5.0714 & 0.0003 \ hline Age & -1.4061 & 2.5988 & -0.5411 & 0.5984 \ hline Tickets & 243.4401 & 43.2470 & 5.6291 & 0.0001 \ hline end{tabular} What is the proportion of the total variability in insurance premiums that can be explained by AGE and TICKETS?

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INSTANT ANSWER

Analyze these data and develop a multiple regression model to predict the number of new subscriptions for a week, based on the number of hours spent on telemarketing and the sales presentation type. Write a report, giving detailed findings concerning the regression model used. The report should include practical interpretations of the major sections of the printout (e.g. Multiple R, R Squared, slopes, etc.). Be sure you present the regression model and make a prediction for a week when formal presentations were made and there were 200 hours spent on telemarketing

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