# Nonparametric procedures can be applied to: A)Categorical data B)Data with an unknown distribution C)Normally-distributed data D)All of these responses are correct

Question
Analyzing categorical data
Nonparametric procedures can be applied to:
A)Categorical data
B)Data with an unknown distribution
C)Normally-distributed data
D)All of these responses are correct

2020-11-06
Step 1
In general nonparametric statistic procedures are inferential procedures and they are not based on any specific distribution or parameter of the data. These procedures are called as distribution free procedures.
Step 2
Therefore, the nonparametric procedures can be applied to categorical data. Thus, correct option is A) Categorical data.
Here, the nonparametric procedures are distribution free procedures. Therefore, options B, C and D are incorrect.

### Relevant Questions

The Bureau of Transportation Statistics Omnibus Household Survey is conducted annually and serves as an information source for the U.S. Department of Transportation. In one part of the survey the person being interviewed was asked to respond to the following statement: "Drivers of motor vehicles should be allowed to talk on a hand-held cell phone while driving." Possible responses were strongly agree, some what agree, some what disagree, and strongly disagree. Forty-four respondents said that they strongly agree with this statement, 120 said that they some what agree, 165 said they some what disagree, and 755 said they strongly disagree with this statement.
Do the responses for this statement provide categorical or quantitative data?
Select the best suitable answer. If none of the choices represents a correct answer, select “Other” and write your own answer. The school cafeteria collects data on students’ juice box selections. This is an example of
A numerical, ordinal data.
B numerical, nominal data.
C categorical, ordinal data.
D categorical, nominal data.
For each of the following variables, indicate whether they are categorical or numerical. Also, write down what type of graph can be drawn for each.
a) Position of a university staff members.
b) Weight of participants.
C Air temperature on the Celsius scale
D) The daily number of code lines written by a programmer
The Kroger Company is one of the largest grocery retailers in the United States, with over 2000 grocery stores across the country. Kroger uses an online customer opinion questionnaire to obtain performance data about its products and services and learn about what motivates its customers (Kroger website, April 2012). In the survey, Kroger customers were asked if they would be willing to pay more for products that had each of the following four characteristics.
The four questions were: Would you pay more for:
products that have a brand name?
products that are environmentally friendly?
products that are organic?
products that have been recommended by others?
For each question, the customers had the option of responding Yes if they would pay more or No if they would not pay more.
a. Are the data collected by Kroger in this example categorical or quantitative?
Which statement best characterizes the definitions of categorical and quantitative data?
Quantitative data consist of numbers, whereas categorical data consist of names and labels that are not numeric.
Quantitative data consist of numbers representing measurements or counts, whereas categorical data consist of names or labels
Quantitative data consist of values that can be arranged in order, whereas categorical data consist of values that cannot be arranged in order.
Quantitative data have an uncountable number of possible values, whereas categorical data have a countable number of possible values.
A wallstreet journal subcriber survey asked 46 questions about subcribers characteristics and interest. State whether each of the following questions provides categorical or quantitative data.
b. Are you male or females?
c. When did you first start reading the WSJ? High school , college, early career, midcareer, late career, or retirement?
d. How long have you been in your present job or position?
e. What type of vehicle are you considering for you next purchase? Nine response categories include sedan, sports car, SUV, minivan, and so on.
1. Find each of the requested values for a population with a mean of $$? = 40$$, and a standard deviation of $$? = 8$$ A. What is the z-score corresponding to $$X = 52?$$ B. What is the X value corresponding to $$z = - 0.50?$$ C. If all of the scores in the population are transformed into z-scores, what will be the values for the mean and standard deviation for the complete set of z-scores? D. What is the z-score corresponding to a sample mean of $$M=42$$ for a sample of $$n = 4$$ scores? E. What is the z-scores corresponding to a sample mean of $$M= 42$$ for a sample of $$n = 6$$ scores? 2. True or false: a. All normal distributions are symmetrical b. All normal distributions have a mean of 1.0 c. All normal distributions have a standard deviation of 1.0 d. The total area under the curve of all normal distributions is equal to 1 3. Interpret the location, direction, and distance (near or far) of the following zscores: $$a. -2.00 b. 1.25 c. 3.50 d. -0.34$$ 4. You are part of a trivia team and have tracked your team’s performance since you started playing, so you know that your scores are normally distributed with $$\mu = 78$$ and $$\sigma = 12$$. Recently, a new person joined the team, and you think the scores have gotten better. Use hypothesis testing to see if the average score has improved based on the following 8 weeks’ worth of score data: $$82, 74, 62, 68, 79, 94, 90, 81, 80$$. 5. You get hired as a server at a local restaurant, and the manager tells you that servers’ tips are $42 on average but vary about $$12 (\mu = 42, \sigma = 12)$$. You decide to track your tips to see if you make a different amount, but because this is your first job as a server, you don’t know if you will make more or less in tips. After working 16 shifts, you find that your average nightly amount is$44.50 from tips. Test for a difference between this value and the population mean at the $$\alpha = 0.05$$ level of significance.
Is statistical inference intuitive to babies? In other words, are babies able to generalize from sample to population? In this study,1 8-month-old infants watched someone draw a sample of five balls from an opaque box. Each sample consisted of four balls of one color (red or white) and one ball of the other color. After observing the sample, the side of the box was lifted so the infants could see all of the balls inside (the population). Some boxes had an “expected” population, with balls in the same color proportions as the sample, while other boxes had an “unexpected” population, with balls in the opposite color proportion from the sample. Babies looked at the unexpected populations for an average of 9.9 seconds (sd = 4.5 seconds) and the expected populations for an average of 7.5 seconds (sd = 4.2 seconds). The sample size in each group was 20, and you may assume the data in each group are reasonably normally distributed. Is this convincing evidence that babies look longer at the unexpected population, suggesting that they make inferences about the population from the sample? Let group 1 and group 2 be the time spent looking at the unexpected and expected populations, respectively. A) Calculate the relevant sample statistic. Enter the exact answer. Sample statistic: _____ B) Calculate the t-statistic. Round your answer to two decimal places. t-statistic = ___________ C) Find the p-value. Round your answer to three decimal places. p-value =
Quantitative/Categorical Data Identify each of the following as quantitative data or categorical data.
a. The platelet counts in Data Set 1 “Body Data” in Appendix B
b. The cigarette brands in Data Set 13 “Cigarette Contents” in Appendix B
c. The colors of the M&M candies in Data Set 27 “M&M Weights” in Appendix B
d. The weights of the M&M candies in Data Set 27 “M&M Weights” in Appendix B
The table below shows the number of people for three different race groups who were shot by police that were either armed or unarmed. These values are very close to the exact numbers. They have been changed slightly for each student to get a unique problem.
Suspect was Armed:
Black - 543
White - 1176
Hispanic - 378
Total - 2097
Suspect was unarmed:
Black - 60
White - 67
Hispanic - 38
Total - 165
Total:
Black - 603
White - 1243
Hispanic - 416
Total - 2262
Give your answer as a decimal to at least three decimal places.
a) What percent are Black?
b) What percent are Unarmed?
c) In order for two variables to be Independent of each other, the P $$(A and B) = P(A) \cdot P(B) P(A and B) = P(A) \cdot P(B).$$
This just means that the percentage of times that both things happen equals the individual percentages multiplied together (Only if they are Independent of each other).
Therefore, if a person's race is independent of whether they were killed being unarmed then the percentage of black people that are killed while being unarmed should equal the percentage of blacks times the percentage of Unarmed. Let's check this. Multiply your answer to part a (percentage of blacks) by your answer to part b (percentage of unarmed).
Remember, the previous answer is only correct if the variables are Independent.
d) Now let's get the real percent that are Black and Unarmed by using the table?
If answer c is "significantly different" than answer d, then that means that there could be a different percentage of unarmed people being shot based on race. We will check this out later in the course.
Let's compare the percentage of unarmed shot for each race.
e) What percent are White and Unarmed?
f) What percent are Hispanic and Unarmed?
If you compare answers d, e and f it shows the highest percentage of unarmed people being shot is most likely white.
Why is that?
This is because there are more white people in the United States than any other race and therefore there are likely to be more white people in the table. Since there are more white people in the table, there most likely would be more white and unarmed people shot by police than any other race. This pulls the percentage of white and unarmed up. In addition, there most likely would be more white and armed shot by police. All the percentages for white people would be higher, because there are more white people. For example, the table contains very few Hispanic people, and the percentage of people in the table that were Hispanic and unarmed is the lowest percentage.
Think of it this way. If you went to a college that was 90% female and 10% male, then females would most likely have the highest percentage of A grades. They would also most likely have the highest percentage of B, C, D and F grades
The correct way to compare is "conditional probability". Conditional probability is getting the probability of something happening, given we are dealing with just the people in a particular group.
g) What percent of blacks shot and killed by police were unarmed?
h) What percent of whites shot and killed by police were unarmed?
i) What percent of Hispanics shot and killed by police were unarmed?
You can see by the answers to part g and h, that the percentage of blacks that were unarmed and killed by police is approximately twice that of whites that were unarmed and killed by police.
j) Why do you believe this is happening?
Do a search on the internet for reasons why blacks are more likely to be killed by police. Read a few articles on the topic. Write your response using the articles as references. Give the websites used in your response. Your answer should be several sentences long with at least one website listed. This part of this problem will be graded after the due date.
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