You wish to test the following claim (HaHa) at a significance level of α=0.001α=0.001. For the context of this problem, μd=μ2−μ1μd=μ2-μ1 where the first data set represents a pre-test and the second data set represents a post-test.

      Ho:μd=0Ho:μd=0
      Ha:μd≠0Ha:μd≠0

You believe the population of difference scores is normally distributed, but you do not know the standard deviation. You obtain pre-test and post-test samples for n=229n=229 subjects. The average difference (post - pre) is ¯d=3.3d¯=3.3 with a standard deviation of the differences of sd=19.4sd=19.4.

What is the critical value for this test? (Report answer accurate to three decimal places.)
critical value = ±±

What is the test statistic for this sample? (Report answer accurate to three decimal places.)
test statistic =

The test statistic is...

• in the critical region
• not in the critical region

This test statistic leads to a decision to...

• reject the null
• accept the null
• fail to reject the null

As such, the final conclusion is that...

• There is sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is not equal to 0.
• There is not sufficient evidence to warrant rejection of the claim that the mean difference of post-test from pre-test is not equal to 0.
• The sample data support the claim that the mean difference of post-test from pre-test is not equal to 0.
• There is not sufficient sample evidence to support the claim that the mean difference of post-test from pre-test is not equal to 0.

Let us suppose that some article studied the probability of death due to burn injuries. The identified risk factors in this study are age greater than 60 years, burn injury in more than 40% of body-surface area, and presence of inhalation injury. It is estimated that the probability of death is 0.003, 0.03, 0.33, or 0.84, if the injured person has zero, one, two, or three risk factors, respectively. Suppose that three people are injured in a fire and treated independently. Among these three people, two people have one risk factor and one person has three risk factors. Let the random variable X denote number of deaths in this fire. Determine the cumulative distribution function for the random variable.

Round your answers to five decimal places (e.g. 98.76543).

F(x)=              with x < 0

F(x)=              with 0 <= x < 1

F(x)=              with 1 <= x < 2

F(x)=              with 2 <= x < 3

F(x)=              with 3 <= x

Hypothesis Testing for a Single Population

Times for a Table

Dominick Aldo owns and operates Carolina’s which is an Italian restaurant in New York. The file Single Population.xlsx is shown below and contains the amount of time that table times varied from table to table.

A) Test the hypothesis that the average table time exceeds 98 minutes using 0.05α=.

B) What is the p-value? Interpret the results.

Be sure that your project shows the following steps

1.Null and alternative hypothesis

2.Determine which distribution to use for the test statistic.

3.Using data provided, calculate necessary sample statistics.

4.Draw a conclusion and interpret the decision.

70 80 100 90 75 60 70 75 110 90 100 75 60 75 80 75 165 60 75 90 110 95 110 150 50 70 90 110 165 60 145 80 115 75 50 90 110 90 100 110 110 85 70 145 120 130 80 90 105 105 100 95 80 100 120 130 75 90 70 125 80 90 95 120 150 195 70 80 110 80 80 85 90 150 60 90 135 170 85 90 120 105 60 70 50 80 100 90 135 120

Please note that for all problems in this course, the standard cut-off (alpha) for a test of significance will be .05, and you always report the exact power unless SPSS output states p=.000 (you’d report p<.001). Also, remember that we divide the p value in half when reporting one-tailed tests with 1 – 2 groups.

1. Paste appropriate SPSS output. (4 pts)

2. Write an APA-style Results section based on your analysis. All homework “Results sections” should follow the examples provided in the presentations and textbooks. They should include the statistical statement within a complete sentence that mentions the type of test conducted, whether the test was significant, and if relevant, effect size and/or post hoc analyses. Don’t forget to include a decision about the null hypotheses. (4 pts)

Consider the following gasoline sales time series data. Click on the datafile logo to reference the data.

a. Using a weight of 1/2 for the most recent observation,1/3 for the second most recent observation, and 1/6 third the most recent observation, compute a three-week weighted moving average for the time series (to 2 decimals). Enter negative values as negative numbers.

b. Compute the MSE for the weighted moving average in part (a).
MSE =

Do you prefer this weighted moving average to the unweighted moving average? Remember that the MSE for the unweighted moving average is 14.39 .
Prefer the unweighted moving average here; it has a - Select your answer -greatersmallerItem 42 MSE.

c. Suppose you are allowed to choose any weights as long as they sum to 1. Could you always find a set of weights that would make the MSE at least as small for a weighted moving average than for an unweighted moving average?
- Select your answer -YesNoItem 43

Kamini, a student of the 1-Year post graduate program at the International School of Business and Design is trying to establish the relationship between compensation (in Rs. Lakh) and years of work experience. She collected data from 9 students who have been placed and fitted a regression equation with Compensation (in Rs. Lakh) as the dependent variable and Years of experience as the independent variable. The Excel output is given below (with some missing values):

Answer the following questions based on the above.

1. What is the value of Regression Sum of Squares?

2. What is the 95% confidence interval for the slope?

3. What is the estimated compensation for a person with 8 years of experience?

4. What is the coefficient of correlation between Compensation and Years of experience?

5. What is the R2 for the above regression equation?

6. What is the t-value corresponding to the intercept?

7. Interpret the value 0.004177 under the column “P-Value”

8. What is the expected compensation for a person with no work experience?

9. The above output provides 95% confidence interval for the intercept. What is the lower limit for the 90% confidence interval for the intercept?

10. The above output provides 95% confidence interval for the intercept. What is the upper limit for the 90% confidence interval for the intercept?

Let us suppose that some article investigated the probability of corrosion of steel reinforcement in concrete structures. It is estimated that the probability of corrosion is 0.19 under specific values of half-cell potential and concrete resistivity. The risk of corrosion in five independent grids of a building with these values of half-cell potential and concrete resistivity. Let the random variable X denote number of grids with corrosion in this building. Determine the cumulative distribution function for the random variable X.

Round your answers to five decimal places (e.g. 98.76543).

f(x)=           with x < 0

f(x)=             with 0 <= x < 1

f(x)=             with 1 <= x < 2

f(x)=             with 2 <= x < 3

f(x)=             with 3 <= x < 4

f(x)=             with 4 <= x < 5

f(x)=             with 5 <= x

Studies have examined changes over time in the annual global temperature based on planet-wide recordings. To make temperatures at different locations comparable, "temperature anomalies" are computed locally by comparing the local annual sea surface temperature average with the local temperature reference, the 1951-1980 average. The analysis showed that, in each of several time periods, the distribution of local seasonal temperature anomalies was approximately Normal. Because temperature anomalies are computed relative to the 1951-1980 reference period, summer temperature N(0,1). Decades later, summer temperature in the northern hemisphere over the 2005-2015 period followed approximately the N(1.6, 1.3) distribution. (a) Draw both distributions on the same graph, indicating the mean and standard deviation of each curve. (Select the graph that best matches the graph you drew. Make sure that the means and standard deviations on the legend match the curves.) 13 (b) In the reference period, standardized summer temperature anomalies greater than 3 were considered to be extreme heat events. Based on the proposed Normal model, what percent of local summer temperature anomalies in the northern hemisphere were extreme heat events in the 1951-1980 reference period? (Enter your answer rounded to one decimal place.) percent: (c) Based on the proposed Normal model, what percent of local summer temperature anomalies in the northern hemisphere between 2005 and 2015 were extreme heat events? (Enter your answer rounded to one decimal place.) percent (d) Based on the recording stations at numerous worldwide locations, 14.5% of temperature anomalies in the northern hemisphere were extreme heat events between 2005 and 2015, compared with 0.1% in the reference period of 1951 to 1980 Compare the actual values to the ones you obtained using the proposed Normal models. O Both values found using the Normal models are very close to the actual values. Neither value found using the Normal models is very close to the actual value. The value found for 1951-1980 using the Normal model is very close to the actual value, but not the one for 2005-201:5 O The value found for 2005-2015 using the Normal model is very close to the actual value, but not the one for 1951-1980.

explain how to detect assignable causes of variation using probability paper

Please use the skills you learned in section 9.2 for this assignment. For this activity, you will be creating a confidence interval for the average number of hours of TV watched. Last semester, my MAT 152 online students asked the question, “How many hours of screen time do you have in a typical week?” Please use the data they collected to answer the following questions. Data: 21, 2, 28, 30, 18, 21, 25, 20, 25, 14, 21, 25, 50, 39, 46, 20, 35, 45, 37, 46

Are there any outliers in this data set?

What calculator test (1-PropZInt, Z-Interval, or T-Interval), Excel, or StatCrunch function will you use to find the confidence interval?

Math 1635 Statistics Probability (Chapter 4) Worksheet

1. If there are 20 marbles marked from 1 to 20 in the bag, what is the probability to pick a marble from the bag and the number can be

(a) divided by 2 or 5

(b) divided by 3 or 7

2. When a card is selected from the deck of 52 cards, find the probability of getting

(a) a spade or a face

(b) a queen or black

(c) a club or an 8

3. When 2 dice are rolled, find the probability of getting

(a) A sum of 7

(b) A sum greater than 8.

(c) A sum less than or equal to 5.

4. A bag contains 2 red, 3 green and 5 white balls. A ball is selected at random and its color is noted. Then it is replaced and another ball is selected and its color is noted. Find the probability of:

(a) selecting 2 green balls

(b) selecting red and then green balls

Two discussion groups are organized by randomly selected employees from each division. During the talks, the director lays out his marketing vision and employees ask questions relevant to their daily work. At the end, each employee has to rate the director on a scale from 1 to 10 (1=very bad; 10=very good). The HR department wants to know if the distribution of ratings of the marketing development employees is different among the employees of the two divisions.

a) Examine the distributions of the ratings (show histograms) by the two groups of employees and explain why a non-parametric test is justified to perform the analysis.

b) Perform an appropriate non-parametric test using a 5% significance level to determine if the distribution of ratings of the marketing development employees is different than that of the marketing operations employees. Specify any assumptions and/or conditions you need to make to apply the test and state your hypothesis clearly. Show your manual calculations.

c) Use Minitab to perform the test in b) above and compare your results

For this activity, you will be creating a confidence interval for the average number of hours of TV watched. Last semester, my MAT 152 online students asked the question, “How many hours of screen time do you have in a typical week?” Please use the data they collected to answer the following questions. Data: 21, 2, 28, 30, 18, 21, 25, 20, 25, 14, 21, 25, 50, 39, 46, 20, 35, 45, 37, 46 Are there any outliers in this data set? What calculator test (1-PropZInt, Z-Interval, or T-Interval), Excel, or StatCrunch function will you use to find the confidence interval? Why do you use this test (and not one of the other 2 tests)?

Here is the full question:

lease use the skills you learned in section 9.2 for this assignment.

For this activity, you will be creating a confidence interval for the average number of hours of TV watched. Last semester, my MAT 152 online students asked the question, “How many hours of screen time do you have in a typical week?” Please use the data they collected to answer the following questions.

Data: 21, 2, 28, 30, 18, 21, 25, 20, 25, 14, 21, 25, 50, 39, 46, 20, 35, 45, 37, 46

1. Are there any outliers in this data set?
2. What calculator test (1-PropZInt, Z-Interval, or T-Interval), Excel, or StatCrunch function will you use to find the confidence interval?
3. Why do you use this test (and not one of the other 2 tests)?
4. Using a 95% confidence level, what is the confidence interval?
5. What is the point estimate for the population mean?
6. What is the margin of error?
7. Suppose you knew the standard deviation for all Americans' screen time was 4 hours. If you wanted your results to be within a margin of error of 0.25 hours, how many people would you have to survey (use a 95% confidence level)?
8. Name at least 2 ways this data could be biased and hence the confidence interval would not be a good estimate of the population mean.

Your final write-up should number (1-8) your answers to each question as well as an explanation of how you arrived at the answers. For example, please include what calculator functions or computations you are using to arrive at the confidence interval.

I realize similar questions were already asked. These aren't the same questions or the same data set. please also explain how to do this in excel.

For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 78, 82, 84, 83, 83, 84, 88, 84, 82, 83, 84, and 83.

1.) Create a three-month moving average forecast against an exponential smoothing forecast with α=.2.

2.) Which forecasting method has the smallest error, use the Mean Square Error (MSE) metric as the measure of model accuracy?

3.) What is the forecast for the 13th month using a three month moving average?