1. Out of a sample of 100 purchase orders, 10 contain errors. What is the confidence interval for 95% confidence?

2. For a 95% confidence level, what is the value n (sample size) when π = .15 and the sampling error is .07?

a.99.96

b.61.47

c. 96.04

d.51.00

A random sample of professional wrestlers was obtained, and the annual salary (in dollars) for each was recorded. The summary statistics were x = 45,500 and n = 17. Assume the distribution of annual salary is normal with o = 8,500.

(a) Find a 90% confidence interval for the true mean annual salary for all professional wrestlers (in dollars). (Round your answers to four decimal places.)

(______________ , ______________) kg

A population consists of the following five values: 2, 2, 30, 9, 30.

a. Not available in Connect.

b. By listing all samples of size 3, compute the mean of the distribution of the sample mean and the population mean. Compare the two values. (Round the final answer to the nearest whole number.)

c. Compare the dispersion in the population with that of the sample means. Hint: Use the range as measure of dispersion.

The dispersion of the population is  (Click to select)  greater  smaller  than that of the sample means.

A population consists of the following five values: 2, 2, 30, 9, 30.

a. Not available in Connect.

b. By listing all samples of size 3, compute the mean of the distribution of the sample mean and the population mean. Compare the two values. (Round the final answer to the nearest whole number.)

c. Compare the dispersion in the population with that of the sample means. Hint: Use the range as measure of dispersion.

The dispersion of the population is  (Click to select)  greater  smaller  than that of the sample means.

1) A random sample of the number of hours worked by 40 employees has a mean of 29.6 hours worked. Assume the population standard deviation is 7.9 hours.

a. Using a 95% confidence level, find the margin of error, E, for the mean number of hours worked.

2) In a study of 265 subjects, the average score on the examination was 63.8. Assume σ = 3.08.

a. What is a 95% confidence interval for ?

3) A college admissions director wishes to estimate the mean age of all students currently enrolled. In a random sample of 20 students, the mean age is found to be 22.9 years. From past studies, the standard deviation is known to be 1.5 years, and the population is normally distributed.

a. Construct a 90% confidence interval of the population mean age.

4) The weight of a product is measured in pounds. A sample of 50 units is taken from a batch. The sample yielded the following results: = 75 lbs., and σ = 10 lbs.

a. Calculate a 99% confidence interval for .

The College Board provided comparisons of SAT scores based on the highest level of education attained by the test taker's parents. A research hypothesis was that students whose parents had attained a higher level of education would on average score higher on the SAT. This data set contains verbal SAT scores for a sample of students whose parents are college graduates and a sample of students whose parents are high school graduates. Use 0.01 as your level of significance.

1. Formulate hypotheses to test the research hypothesis. Let population 1 be the students whose parents are college graduates and let population 2 be students whose parents are high school graduates.
2. Is this an one-tailed or two-tailed test?
3. Use Excel to test your hypotheses. What is the test statistic?
4. What is the p-value?
5. What is the critical value?
6. What is your conclusion using 0.01 as the level of significance?
7. Explain your conclusion in the context of the problem (i.e. in terms a non-statistician could understand).

In what follows use any of the following tests/procedures: Regression, multiple regression, confidence intervals, one sided T-test or two sided T-test. All the procedures should be done with 5% P-value or 95% confidence interval.Some answers are approximated, choose the most appropriate answer.Open Pollution data. SETUP: Is it reasonable to claim that cities with precipitation of less than 100 days have average temperature of less than 65 degrees F? Given the data your job is to confirm or disprove this claim.

I. What test/procedure did you perform? (6.66 points)

• a. One sided T-test
• b. Two sided T-test
• c. Regression
• d. Confidence interval

II. Statistical interpretation? (6.66 points)

• a. Since P-value is small we are confident that the slope is not zero.
• b. Since P-value is small we are confident that the averages are different.
• c. Since P-value is too large the test is inconclusive.
• d. None of these.

III. Conclusion? (6.66 points)

• a. Yes, this is a reasonable claim.
• b. No, we cannot confirm that this is a reasonable claim.

  CITY    SO2     MANUF   POP     TEMP    WIND    PRECIP-INCHES   PRECIP-#DAYS
  Phoenix 11      213     582     70.3    6       7.05    36
  Little Rock     15      91      132     61      8.2     48.52   100
  San Francisco   16      453     716     56.7    8.7     20.66   67
  Denver  24      454     515     51.9    9       12.95   86
  Hartford        82      412     158     49.1    9       43.37   127
  Wilmington      43      80      80      54      9       40.25   114
  Washington      30      434     757     57.3    9.3     38.89   111
  Jacksonville    18      136     529     68.4    8.8     54.47   116
  Miami   14      207     335     75.5    9       59.8    128
  Atlanta 32      368     497     61.5    9.1     48.34   115
  Chicago 131     3344    3369    50.6    10.4    34.44   122
  Indianapolis    40      361     746     52.3    9.7     38.74   121
  Des Moines      20      104     201     49      11.2    30.85   103
  Wichita 10      125     277     56.6    12.7    30.58   82
  Louisville      35      291     593     55.6    8.3     43.11   123
  New Orleans     9       204     361     68.3    8.4     56.77   113
  Baltimore       47      625     905     55      9.6     41.31   111
  Detroit 46      1064    1513    49.9    10.1    30.96   129
  Minneapolis-St. Paul    42      699     744     43.5    10.6    25.94   137
  Kansas City     18      381     507     54.5    10      37      99
  St. Louis       61      775     622     55.9    9.5     35.89   105
  Omaha   17      181     347     51.5    10.9    30.18   98
  Albuquerque     15      46      244     56.8    8.9     7.77    58
  Albany  56      44      116     47.6    8.8     33.36   135
  Buffalo 11      391     463     47.1    12.4    36.11   166
  Cincinnati      27      462     453     54      7.1     39.04   132
  Cleveland       80      1007    751     49.7    10.9    34.99   155
  Columbus        27      266     540     51.5    8.6     37.01   134
  Philadelphia    79      1692    1950    54.6    9.6     39.93   115
  Pittsburgh      63      347     520     50.4    9.4     36.22   147
  Providence      136     343     179     50      10.6    42.75   125
  Memphis 10      337     624     61.6    9.2     49.1    105
  Nashville       23      275     448     59.4    7.9     46      119
  Dallas  11      641     844     66.2    10.9    35.94   78
  Houston 10      721     1233    68.9    10.8    48.19   103
  Salt Lake City  28      137     176     51      8.7     15.17   89
  Norfolk 38      96      308     59.3    10.6    44.68   116
  Richmond        38      197     299     57.8    7.6     42.59   115
  Seattle 40      379     531     51.1    9.4     38.79   164
  Charleston      40      35      71      55.2    6.5     40.75   148
  Milwaukee       20      569     717     45.7    11.8    29.07   123

NOTE :- Please find the probabilities as functions of cost

A service facility charges a $20 fixed fee plus $25 per hour of service up to 6 hours, and no additional fee is charged for a service visit exceeding 6 hours. Suppose that the service time τ again ranges from 0 to 10 hours, but now the probability density is twice as large during the middle 6 hours [2, 8] than during the outer 4 hours [0, 2] and [8, 10]. (Note as before that τ is a continuous random variable.) Let X represent the cost of service in the facility.

We would like to set up the probability density function (PDF) and the cumulative distribution function (CDF), then use them to analyze service fees.

Design Specifications

1. Sketch the probability density as a function of time. Be quantitative, and pay attention to units. Compute the probability that the service is greater than 6 hours. Then, sketch the probability density as a function of cost. Again, be quantitative and pay attention to units

2. Use the probability density function to set up the cumulative probability, also as a function of X.

1. The following table gives the systolic blood pressure and age of patients.

1. a) Determine an r value for this data and classify the value as weak, moderate, or strong.

2. b) Based on your calculated r value, what can you say about the slope of the regression line?

3. c) Determine the model equation. This is also called the regression line or the least squares line.

4. d) Refer to your notes around the assumptions of SLR. What is the value of∑ ? ? What is the mean of the error terms? How are the error terms distributed?

5. e) Calculate the values of the residuals and sum them.

6. f) Calculate the standard error, ?!, and ?", and describe the meaning of ?".

7. g) Conduct a hypothesis test at the 5% level of significance to test if the slope is significantly different from 0. What is the p – value? Determine a 95% confidence for ?#.

8. h) Suppose we want to predict the sbp for an average Age = 31. What would a 95% confidence interval be? (Notice that although the word predict is in the question, it specifically asks for the confidence interval.)

9. i) To predict the sbp, Y, for a person drawn at random who is aged 31, X, we would have 95% confidence in what interval? (Notice here the word confidence is used but it never specifically asks for a “confidence interval”. It just says 95% confidence in what interval. Here we are asking for a prediction interval)

Give an example of a stochastic process that is:

(a) Both a Markov process and a martingale.

(b) A Markov process but not a martingale.

(c) A martingale but not a Markov process.

(d) Neither a Markov process nor a martingale.

give the difference between anova, manova,mancova,pathanalysis,t-test,multiple regression and logistic regression

answrr only if you know otherwise dislike

Production volume

400

450

550

600

700

750

Total cost

4000

5000

5400

5900

6400

7000

. A new vaccination is being used in a laboratory experiment to investigate whether it is effective. There are 252 subjects in the study. Is there sufficient evidence to determine if vaccination and disease status are related?

Vaccination Status     Diseased      Not Diseased       Total

Vaccinated                      51)               54)                    105)

Not Vaccinated    54)               73)                    147)

Total              (125)    (127)    ( 252)

State the null and alternative hypothesis.

Find the value of the test statistic. Round your answer to three decimal places.

Find the degrees of freedom associated with the test statistic for this problem.

Find the critical value of the test at the 0.01 level of significance. Round your answer to three decimal places.

Make the decision to reject or fail to reject the null hypothesis at the 0.01 level of significance.

State the conclusion of the hypothesis test at the 0.01 level of significance.

Define each of the following definitions concerning data:

Statistics, Skewed distribution, Histogram, Outliers, Sample space and Continuous variable

Use SPSS, Excel or Minitab software to answer the following questions.

Generate normal random data with sample size, n = 40, mean = 20 and standard deviation = 11. Write the generated data in the following table.

Answer:

1. Conduct the descriptive statistics for center and dispersion. Interpret your results!

Answer:

2. Construct a 90% confidence interval for the average. Interpret your results!

Answer

3. Construct the histogram, boxplot, and stem and leaf graphical charts. Is the data approximately bell-shaped? Are there outliers? Explain!

Answer

a) A sample of 8 observations collected in a regression study on two variables, x(independent variable) and y(dependent variable). The sample resulted in the following data.

SSR=66, SST=86

Calculate an unbiased estimate of the variance of the error term epsilon.

b) A sample of 11 observations collected in a regression study on two variables, x(independent variable) and y(dependent variable). The sample resulted in the following data.

SSE=22, SSR=64

Calculate the coefficient of determination for the developed estimated regression equation.

c) A sample of 11 observations collected in a regression study on two variables, x(independent variable) and y(dependent variable). The sample resulted in the following data.

SSR=76, SST=83,  summation (x_i-xbar)²=25, summation (x_i-xbar)(y_i-ybar)=49.

Calculate the t test statistics to determine whether a statistically linear relationship exists between x and y.

d)

A sample of 8 observations collected in a regression study on two variables, x(independent variable) and y(dependent variable). The sample resulted in the following data.

SSR=73, SST=86

Calculate the F test statistics to determine whether a statistically linear relationship exists between x and y.