agree or not?

What is a nonparametric test? What is a parametric analysis?

Parametric tests assume underlying statistical distributions in the data. Therefore, several conditions of validity must be met so that the result of a parametric analysis is reliable. The student’s t-test for two independent samples is safe only if each sample follows a normal distribution and if sample variances are homogeneous. Nonparametric tests do not rely on any delivery. They can thus be applied even if parametric conditions of validity are not met. Parametric tests often have nonparametric equivalents. You will find different parametric tests with their equivalents when they exist in this grid. 3.

what is the difference between a nonparametric test and a distribution-free test?

While nonparametric tests don’t assume that your data follow a normal distribution, they do have other assumptions that can be hard to meet. For nonparametric tests that compare groups, a common assumption is that the data for all groups must have the same spread dispersion. If your groups have a different spread, the nonparametric tests might not provide valid results. On the other hand, if you use the 2-sample t-test or One-Way ANOVA, you can simply go to the Options sub dialog and uncheck Assume equal variances. Voilà, you’re good to go even when the groups have different spreads.

6) Provide an example of counting in your everyday life. Think of an example where you could use a counting method and describe the method.

I'm having trouble applying bayes formula with the following multi-part question

In April 2013, the total sales from General Motors, Ford, or Chrysler was 606,334 cars or light trucks. The probability that the vehicle sold was made by General Motors was 0.392, by Ford 0.350, by Chrysler 0.258. Additionally, the probability that a General Motors vehicle sold was a car was 0.395, a Ford vehicle sold was a car was 0.370, and a Chrysler vehicle sold was a car was 0.332.

(1) Given the vehicle sold was a car, find the probability it was made by General Motors

(a) About 0.332 ; (b) About 0.274 ; (c) About 0.376 ; (d) About 0.232 ; (e) About 0.418 ;

(2) Given the vehicle sold was a car, find the probability it was made by Chrysler.

(a) About 0.376 ; (b) About 0.232 ; (c) About 0.332 ; (d) About 0.274 ; (e) About 0.418 ;

(3) Given the vehicle sold was a light truck, find the probability it was made by General Motors.

(a) About 0.418 ; (b) About 0.232 ; (c) About 0.376 ; (d) About 0.274 ; (e) About 0.332 ;

(4) Given the vehicle sold was a light truck, find the probability it was made by Chrysler.

(a) About 0.274 ; (b) About 0.332 ; (c) About 0.418 ; (d) About 0.232 ; (e) About 0.376 ;

Use Statkey for the following numbers:

18 54 64 46 91 38 25 45 67 57 48 44 63

83 84 79 52 54 41 52 56 76 41 75 79 68

28 55 77 68 33 65 59 37 61 70 47 51 32

56 19 45 29 63 75 39 84 48 42 36

1. Does this data come from a "mound-shaped", distribution? Justify your answer.

2. Is the data symmetric or skewed? Justify your answer.

3. Are there any TRUE outliers, what are they, and what percent of the sample are they? Justify your answer.

4. Bell-shaped (normal) sample? why?

On April 1, 1992, New Jersey’s minimum wage was increased from $4.25 to $5.05 per hour, while the minimum wage in Pennsylvania stayed at $4.25 per hour. Energetic students collected data on 410 fast food restaurants in New Jersey (the treatment group) and eastern Pennsylvania (the control group). The “before” period is February 1992, and the “after” period is November 1992. Using these data, we will estimate the effect of the “treatment,” raising the New Jersey minimum wage on employment at fast food restaurants in New Jersey (i.e., H_0:δ=0 versus H_A:δ<0). It is easier and more general to use the regression format to compute the differences-in-differences estimate using sample means. Let y=FTE employment , the treatment variable is the indicator variable NJ=1 if observation is from New Jersey, and zero if from Pennsylvania. The time indicator is D=1 if the observation is from November and zero if it is from February. (a.)Write out the regression equation. (b)Report the least squares estimates . (c)At the α=.05 level of significance the regression region for the left tail test in above hypotheses is t≤-1.645, what is your conclusion? (d)As with randomized control (quasi) experiments it is interesting to see the robustness of the result from (c). Please, add indicator variables for fast food chain and whether the restaurant was company-owned rather than franchise-owned. These changes alter the DID estimator? (e)Please, add indicator variables for geographical regions within the survey area. These changes alter the DID estimator?

Case 1 Instruction (Accounting Application) Use the MS Excel tabular graphical methods of descriptive statistics to summarize the sample data in the data set named PelicanStores in Case 1 folder. The managerial report should contain summaries such as:

1. A frequency and relative frequency distributions for the methods of payment (different cards). (20%)

2. Mean, median, first quartile, third quartile, and sample standard deviation for net sales from regular customers. (20%)

3. Mean, median, first quartile, third quartile, and sample standard deviation for net sales from married female. (20%)

4. Apply the location method to calculate the 60th percentile manually of net sales for each method (card) of payment. Please indicate which card has the highest 60th percentile and show the process. (20%)

5. Apply Chebyshev’s Theorem to calculate the range (i.e. $ to $) of at least 75% of the net sales must fall within for the Proprietary Card payment. (20%) (Hint: What is the z-score for at least 75% of data range?)

An economist wonders if corporate productivity in some countries is more volatile than in other countries. One measure of a company's productivity is annual percentage yield based on total company assets.

A random sample of leading companies in France gave the following percentage yields based on assets.

Use a calculator to verify that the sample variance is s² ≈ 2.046 for this sample of French companies.

Another random sample of leading companies in Germany gave the following percentage yields based on assets.

Use a calculator to verify that s² ≈ 1.044 for this sample of German companies.

Test the claim that there is a difference (either way) in the population variance of percentage yields for leading companies in France and Germany. Use a 5% level of significance. How could your test conclusion relate to the economist's question regarding volatility (data spread) of corporate productivity of large companies in France compared with companies in Germany? (a) What is the level of significance?

State the null and alternate hypotheses.

H_o: σ₁² = σ₂²; H₁: σ₁² > σ₂²H_o: σ₁² > σ₂²; H₁: σ₁² = σ₂²     H_o: σ₂² = σ₁²; H₁: σ₂² > σ₁²H_o: σ₁² = σ₂²; H₁: σ₁² ≠ σ₂²

(b) Find the value of the sample F statistic. (Use 2 decimal places.)


What are the degrees of freedom?

What assumptions are you making about the original distribution?

The populations follow independent chi-square distributions. We have random samples from each population. The populations follow independent normal distributions. We have random samples from each population.     The populations follow independent normal distributions. The populations follow dependent normal distributions. We have random samples from each population.

(c) Find or estimate the P-value of the sample test statistic. (Use 4 decimal places.)

p-value > 0.200 0.100 < p-value < 0.200     0.050 < p-value < 0.100 0.020 < p-value < 0.050 0.002 < p-value < 0.020 p-value < 0.002

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis?

At the α = 0.05 level, we reject the null hypothesis and conclude the data are not statistically significant. At the α = 0.05 level, we reject the null hypothesis and conclude the data are statistically significant.     At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are not statistically significant. At the α = 0.05 level, we fail to reject the null hypothesis and conclude the data are statistically significant.

(e) Interpret your conclusion in the context of the application.

Fail to reject the null hypothesis, there is sufficient evidence that the variance in percentage yields on assets is greater in the French companies. Reject the null hypothesis, there is insufficient evidence that the variance in percentage yields on assets is greater in the French companies.     Reject the null hypothesis, there is sufficient evidence that the variance in percentage yields on assets is different in both companies. Fail to reject the null hypothesis, there is insufficient evidence that the variance in percentage yields on assets is different in both companies.

A highway department executive claims that the number of fatal accidents which occur in her state does not vary from month to month. The results of a study of 158 fatal accidents were recorded. Is there enough evidence to reject the highway department executive's claim about the distribution of fatal accidents between each month?

Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fatal Accidents 17 10 12 19 9 10 10 12 12 18 17 12

Step 1 of 10: State the null and alternative hypothesis. Step 2 of 10: What does the null hypothesis indicate about the proportions of fatal accidents during each month? Step 3 of 10: State the null and alternative hypothesis in terms of the expected proportions for each category. Step 4 of 10: Find the expected value for the number of fatal accidents that occurred in January. Round your answer to two decimal places. Step 5 of 10: Find the expected value for the number of fatal accidents that occurred in April. Round your answer to two decimal places. Step 6 of 10: Find the value of the test statistic. Round your answer to three decimal places. Step 7 of 10: Find the degrees of freedom associated with the test statistic for this problem. Step 8 of 10: Find the critical value of the test at the 0.1 level of significance. Round your answer to three decimal places. Step 9 of 10: Make the decision to reject or fail to reject the null hypothesis at the 0.1 level of significance. Step 10 of 10: State the conclusion of the hypothesis test at the 0.1 level of significance.

The Graduate Record Examination (GRE) is a test required for admission to many U.S. graduate schools. Students' scores on the quantitative portion of the GRE follow a normal distribution with mean 150 and standard deviation of 8.8. In addition to other qualifications, a score of at least 160 is required for admission to a particular graduate school.

a. What proportion of combined scores can be expected to be over 160?

b. What proportion of combined GRE scores can be expected to be between 155 and 160?

c. What is the probability that a randomly selected student will score less than 150 points?

d. Historically, Department of History at NYU has admitted students whose quantitative GRE score is at least at the 61st percentile. What is the lowest GRE score of the students they admit?

e. Determine the range of scores that make up the middle 95% of the scores.

Twemty subgroups of size 5 are obtained for the purpose of determining trial control limits for mean and an R-chart.

A.) Determine the rial control limits for each chart. B.) Explain why there are so many subgroups averages outside the control limits for the mean chart in spite of the fact that the averages do not vary greatly. C.) What should be done with those subgroups whose averages is beyond the limits. D.) Since the number of points outside the control limits on the mean chart is quite high relative to the number of points that are plotted, what might this suggest about the type of distruibution from which the data could have come.

Hypothesis Testing and Confidence Intervals for Proportions and Hypothesis Test for Difference between Two Means

A pharmaceutical company is testing a new cold medicine to determine if the drug has side affects. To test the drug, 8 patients are given the drug and 9 patients are given a placebo (sugar pill). The change in blood pressure after taking the pill was as follows:

Given drug: 3 4 5 1 -2 3 5 6

Given placebo: 1 -1 2 7 2 3 0 3 4

Test to determine if the drug raises patients’ blood pressure more than the placebo using  = 0.01

Begin this discussion by first stating your intended future career. Then give an example from your intended future career of a Population Mean that you would like to do a Hypothesis Test for. The target Population of your Hypothesis Test activities must be included in your discussion along with the unit of measurement that you are using. As shown in the text your Null and Alternative hypothesis MUST include the symbol for a Population Mean along with your hypothesized claimed numerical value for this parameter.

How much money do winners go home with from the television quiz show Jeopardy? To determine an answer, a random sample of winners was drawn and the amount of money each won was recorded and listed below. Estimate with 92% confidence the mean winning's for all the show's players.

34135 29640 26440 19111 34635 24903 20591 34012 33338 23721 19518 32867 21627 17659 28450 34135 19111 20591 23721 21627 29640 34635 34012 19518 17659 26440 24903 33338 32867 28450

Upper confidence limit =

Lower confidence limit =

A television cable company receives numerous phone calls throughout the day from customers reporting service troubles and from would-be subscribers to the cable network. Most of these callers are put “on hold” until a company operator is free to help them. The company has determined that the length of time a caller is on hold is normally distributed with a mean of 3.1 minutes and a standard deviation 0.9 minutes. Company experts have decided that if as many as 5% of the callers are put on hold for 4.8 minutes or longer, more operators should be hired. a. What proportion of the company’s callers are put on hold for more than 4.8 minutes? Should the company hire more operators? Show these probabilities on a sketch of the normal curve. b. At another cable company (length of time a caller is on hold follows the same distribution as before), 2.5% of the callers are put on hold for longer than x minutes. Find the value of x, and show this on a sketch of the normal curve.