A city council suspects a judge of being a "hanging judge" because s/he is perceived as imposing harsher penalties for the same sentence. To investigate this, a random sample of 45 cases is taken from the judge's prior cases that resulted in a guilty verdict for a certain crime. The average jail sentence s/he imposed for the sample is 25 months. The average jail sentence for the same type of crimes is 23 months with a standard deviation of 13 months. What can be concluded with α = 0.01?

What is the appropriate test statistic?
---Select--- na

z-test

one-sample t-test

independent-samples t-test

related-samples t-test

Compute the appropriate test statistic(s) to make a decision about H₀.
(Hint: Make sure to write down the null and alternative hypotheses to help solve the problem.)
critical value =   ; test statistic =  

If appropriate, compute the CI. If not appropriate, input "na" for both spaces below.
[   ,   ]

e) Compute the corresponding effect size(s) and indicate magnitude(s).
If not appropriate, input and select "na" below.
d =   ;   ---Select--- na trivial effect small effect medium effect large effect
r² =   ;   ---Select--- na trivial effect small effect medium effect large effect

This investigation will involve measuring how high people can jump. Use of tools, such as tape measures and rulers, should be considered.

1. Collect data.

2. Calculate the means and the five-number summaries for the entire sample and for each of your categories of the qualitative variable (e.g., for male and for female) and make a chart that presents those statistics.

3. Create comparative boxplots for the different groups (e.g., male and female).

4. Describe where your own jump-height falls in relation to your data sets. Use measures of position such as percentile and quartile.

5. Consider jump-heights and the qualitative variable you have chosen. Discuss and determine which should be the independent and which should be the dependent variable. Then create a scatterplot.  

The data can be made up, but please make it accurate (dont say that a person jumped a mile in height). Let the sample size be at least 10.

1.Which of the following scenarios would it be appropriate to use a normal approximation for the sampling distribution of the sample proportion?

Select one:

a.) A researcher wishes to find the probability that more than 60% of a sample of undergraduate students from UNC will be female. She samples the first 42 students that walk into the gym on Monday morning. The population proportion of undergraduate females at UNC is known to be 60.1%.

b.)A researcher wishes to find the probability that less than 5% of a sample of undergraduate students from Appalachian State University will be between the ages of 25 and 34. He randomly samples 50 undergraduate students from the student database. The proportion of undergraduates between the ages of 25 and 34 is 5.3%.

c.)A grad student at NC state wants to know how likely it is that a group of students would be made up of more than 27% graduate students. She will randomly select 38 students and ask them if they are a graduate student or an undergraduate student. The population proportion of grad students at NC state is 26.6%.

d.)A full-time student at Fayetteville State University wants to know how likely it is that a group of students would be made up of less than 70% full-time students. She will ask 30 people that she sees parking in the parking deck if they are full-time or part-time. The population of full-time students at Fayetteville State is known to be 72%.

2. In the general population in the US, identical twins occur at a rate of 30 per 1,000 live births. A survey records 10,000 births during Jan 2018 to Jan 2019 and found 400 twins in total. Which of the following are true?

Select one or more:

The proportion of twin births during Jan 2018 to Jan 2019 is .03.

The proportion of twin births during Jan 2018 to Jan 2019 is .04.

The probability of twin births among the general population is .03.

The probability of twin births among the general population is .04.

Pr(observing a sample proportion of twin births from a random sample of 10,000 live births <= 0.04) = 0.03.

Pr(observing a sample proportion of twin births from a random sample of 10,000 live births <= 0.04) = 0.5.

Pr(observing a sample proportion of twin births from a random sample of 10,000 live births <= 0.03) = 0.04.

Pr(observing a sample proportion of twin births from a random sample of 10,000 live births <= 0.03) = 0.5.

Twenty-nine percent of primary care doctors think their patients receive unnecessary medical care. If required, round your answer to four decimal places. (a) Suppose a sample of 300 primary care doctors was taken. Show the distribution of the sample proportion of doctors who think their patients receive unnecessary medical care.

For the year 2009, the table below gives the percent of people living below the poverty line in the 26 states east of the Mississippi River. Answer the following questions based on this data. State Percent Alabama 7.5 Connecticut 7.9 Delaware 14.9 Florida 13.2 Georgia 12.1 Illinois 10.0 Indiana 9.9 Kentucky 11.9 Maine 13.3 Maryland 10.9 Massachusetts 7.9 Michigan 15.8 Mississippi 9.1 State Percent New Hampshire 14.6 New Jersey 8.3 New York 9.1 North Carolina 12.1 Ohio 13.6 Pennsylvania 10.5 Rhode Island 8.2 South Carolina 12.5 Tennessee 10.0 Vermont 7.3 Virginia 10.4 West Virginia 10.5 Wisconsin 16.1 Find the five-number summary for this data.

I am trying to find an appropriate statistical test to run for a research study using someone else's gathered data (so that no IRB process is needed). In their data they present:

Likelihood of Falling Asleep:

Never 17

Seldom 22

Moderate 15

High 12

Use of napping during duty:

Never 27

Rarely 19

Sometimes 16

Often 4

To simplify I think that it would probably be beneficial to group these as:

Likelihood of Falling Asleep

Never: 17

Yes: 49

Use of Napping During Duty:

Never: 27

Yes: 39

So variables are:

Likelihood of Falling Asleep

Use of Naps on Duty

Hypothesis:

Null hypothesis: Likelihood of Falling Asleep and variable Use of napping during duty are independent of each other.

Alternative hypothesis: Likelihood of Falling Asleep and variable Use of napping during duty are not independent.

Both of these seem to be independent variables, but is there a way to show a relationship (or lack thereof) without a dependent variable. In this case the dependent variable could be "pilot" of which 66 were surveyed for the study that I am taking the data from. Trying accurately to show whether or not the likelihood of falling asleep in the cockpit is related to whether or not the pilot naps on duty outside of the cockpit.

I think a Chi Square would be a way to attempt to show whether or not a relationship exists, however I get stuck when I input data into stat crunch as a chi square compares the actual data to what we expect should happen (in this case 33/33). Is there a good way to test the two against each other or to show possible relationships?

Thanks!

You may believe that the population proportion of adults in the US who own SUVs is 0.25. Your data is that you surveyed people leaving work at the end of the day and found that 5 out of 18 owned an SUV. Test this at the .05 significance level. In addition to the significance level, what is the the mean and standard deviation?

Total plasma volume is important in determining the required plasma component in blood replacement therapy for a person undergoing surgery. Plasma volume is influenced by the overall health and physical activity of an individual. Suppose that a random sample of 42 male firefighters are tested and that they have a plasma volume sample mean of x = 37.5 ml/kg (milliliters plasma per kilogram body weight). Assume that σ = 7.00 ml/kg for the distribution of blood plasma.

(a) Find a 99% confidence interval for the population mean blood plasma volume in male firefighters. What is the margin of error? (Round your answers to two decimal places.)

(b) What conditions are necessary for your calculations? (Select all that apply.)

the distribution of weights is normalσ is unknownn is largethe distribution of weights is uniformσ is known

(c) Interpret your results in the context of this problem.

99% of the intervals created using this method will contain the true average blood plasma volume in male firefighters.1% of the intervals created using this method will contain the true average blood plasma volume in male firefighters.     The probability that this interval contains the true average blood plasma volume in male firefighters is 0.01.The probability that this interval contains the true average blood plasma volume in male firefighters is 0.99.

(d) Find the sample size necessary for a 99% confidence level with maximal margin of error E = 2.10 for the mean plasma volume in male firefighters. (Round up to the nearest whole number.)
male firefighters

Thirty-three small communities in Connecticut (population near 10,000 each) gave an average of x = 138.5 reported cases of larceny per year. Assume that σ is known to be 43.7 cases per year. (a) Find a 90% confidence interval for the population mean annual number of reported larceny cases in such communities. What is the margin of error? (Round your answers to one decimal place.) lower limit upper limit margin of error (b) Find a 95% confidence interval for the population mean annual number of reported larceny cases in such communities. What is the margin of error? (Round your answers to one decimal place.) lower limit upper limit margin of error (c) Find a 99% confidence interval for the population mean annual number of reported larceny cases in such communities. What is the margin of error? (Round your answers to one decimal place.) lower limit upper limit margin of error (d) Compare the margins of error for parts (a) through (c). As the confidence levels increase, do the margins of error increase? As the confidence level increases, the margin of error remains the same. As the confidence level increases, the margin of error decreases. As the confidence level increases, the margin of error increases. (e) Compare the lengths of the confidence intervals for parts (a) through (c). As the confidence levels increase, do the confidence intervals increase in length? As the confidence level increases, the confidence interval decreases in length. As the confidence level increases, the confidence interval remains the same length. As the confidence level increases, the confidence interval increases in length.

(1 point) (NOTE: You will be limited to no more than 4 attempts for credit for this problems.)

Rework problem 13 from section 3.2 of your text, involving Example 3.9, with the changes described below.

Suppose you have a bag containing five black balls numbered 1, 2, 3, 4, 5, four blue balls numbered 6, 7, 8, 9, and seven green balls numbered 10, 11, 12, 13, 14, 15, 16.

Fill each of the following blanks with a Y for yes or an N for no:

(1) Is the event "drawing a black ball" independent from the event "drawing an even-numbered ball"?

(2) Is the event "drawing a black ball" independent from the event "drawing an odd-numbered ball"?

(3) Is the event "drawing a blue ball" independent from the event "drawing an even-numbered ball"?

(4) Is the event "drawing a blue ball" independent from the event "drawing an odd-numbered ball"?

(5) Is the event "drawing a green ball" independent from the event "drawing an even-numbered ball"?

(6) Is the event "drawing a green ball" independent from the event "drawing an odd-numbered ball"?

Researchers watched groups of dolphins off the coast of Ireland in 1998 to determine what activities the dolphins partake in at certain times of the day. The numbers in the Table below represent the number of groups of dolphins that took part in an activity at certain times of days. In Excel

1. Calculate the probability (in reduced fraction form) that a dolphin group is involved with travel.
2. Calculate the probability (in reduced fraction form) that a dolphin group is around in the morning.
3. Calculate the probability (in reduced fraction form) that a dolphin group is involved with travel, given that it is morning.
4. Calculate the probability (in reduced fraction form) that a dolphin group is around in the morning, given that it is socializing.
5. Calculate the probability (in reduced fraction form) that a dolphin group is around in the afternoon, given that it is feeding.
6. Calculate the probability (in reduced fraction form) that a dolphin group is either around in the evening or is feeding.

(1 point) Rework problem 17 from section 3.2 of your text, involving the sum of the numbers showing on two fair six-sided dice.

(1) What is the probability that exactly one die shows a 5 given that the sum of the numbers is 10?

(2) What is the probability that the sum of the numbers is 10 given that exactly one die shows a 5?

(3) What is the probability that the sum of the numbers is 10 given that at least one die shows a 5?

Define the data you ( Any Date set could be used ) want to study in order to solve a problem or meet an objective:

Find a data-set and analyse it for a project. to answer following questions:

What are the observations (Cases)?

What are the variables?

Variables are qualitative or quantitative define?

What interesting questions could it help you answer?

Please share the screen shot of the data.

High in the Rocky Mountains, a biology research team has drained a lake to get rid of all fish. After the lake was refilled, they stocked it with an endangered species of Greenback trout. Of the 2000 Greenback trout put into the lake 800 were tagged for later study. An electroshock method is used on individual fish to get a study sample. However, this method is hard on the fish. The research team wants to know the smallest number of fish that must be electroshocked to be at least 80% sure of getting a sample of two or more tagged trout. Please provide the answer. For more studies similar to this one, see A National Symposium on Catch and Release Fishing, Humboldt State University.