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26 . In a survey of 80 males, 45 had played an organized sport growing up. Of the 70 females surveyed, 25 had played an organized sport growing up. We are interested in whether the proportion for males is higher than the proportion for females. The correct conclusion is that:

  1. there is insufficient information to conclude that the proportion for males is the same as the proportion for females.
  2. there is insufficient information to conclude that the proportion for males is not the same as the proportion for females.
  3. there is sufficient evidence to conclude that the proportion for males is higher than the proportion for females.
  4. not enough information to make a conclusion.

27 . From past experience, a statistics teacher has found that the average score on a midterm is 81 with a standard deviation of 5.2. This term, a class of 49 students had a standard deviation of 5 on the midterm. Do the data indicate that we should reject the teacher’s claim that the standard deviation is 5.2? Use α = 0.05.

  1. Yes
  2. No
  3. Not enough information given to solve the problem

28 . Three loading machines are being compared. Ten samples were taken for each machine. Machine I took an average of 31 minutes to load packages with a standard deviation of two minutes. Machine II took an average of 28 minutes to load packages with a standard deviation of 1.5 minutes. Machine III took an average of 29 minutes to load packages with a standard deviation of one minute. Find the p -value when testing that the average loading times are the same.

  1. p -value is close to zero
  2. p -value is close to one
  3. not enough information given to solve the problem

Use the following information to answer the next three exercises: A corporation has offices in different parts of the country. It has gathered the following information concerning the number of bathrooms and the number of employees at seven sites:

Number of employees x 650 730 810 900 102 107 1150
Number of bathrooms y 40 50 54 61 82 110 121

29 . Is the correlation between the number of employees and the number of bathrooms significant?

  1. Yes
  2. No
  3. Not enough information to answer question

30 . The linear regression equation is:

  1. ŷ = 0.0094 − 79.96 x
  2. ŷ = 79.96 + 0.0094 x
  3. ŷ = 79.96 − 0.0094 x
  4. ŷ = − 0.0094 + 79.96 x

31 . If a site has 1,150 employees, approximately how many bathrooms should it have?

  1. 69
  2. 91
  3. 91,954
  4. We should not be estimating here.

32 . Suppose that a sample of size ten was collected, with x ¯ = 4.4 and s = 1.4. H 0 : σ 2 = 1.6 vs. H a : σ 2 ≠ 1.6. Which graph best describes the results of the test?

There are 4 curves that display the P-value for a Test of a Single Variance. Graph (a) shows two tails shaded for chi-square = 6.89. Graph (b) shows two tails shaded for chi-square = 1.96. Graph (c) shows two tails shaded for chi-square = 11.03. Graph (d) shows two tails shaded for chi-square = 2.23.

Sixty-four backpackers were asked the number of days since their latest backpacking trip. The number of days is given in [link] :

# of days 1 2 3 4 5 6 7 8
Frequency 5 9 6 12 7 10 5 10

33 . Conduct an appropriate test to determine if the distribution is uniform.

  1. The p -value is>0.10. There is insufficient information to conclude that the distribution is not uniform.
  2. The p -value is<0.01. There is sufficient information to conclude the distribution is not uniform.
  3. The p -value is between 0.01 and 0.10, but without alpha ( α ) there is not enough information
  4. There is no such test that can be conducted.

34 . Which of the following statements is true when using one-way ANOVA?

  1. The populations from which the samples are selected have different distributions.
  2. The sample sizes are large.
  3. The test is to determine if the different groups have the same means.
  4. There is a correlation between the factors of the experiment.

Practice final exam 2 solutions


1 . b. parameter.

2 . a.

3 . c. seven

4 . c. 0.02

5 . c. none of the above

6 . d. 100 140

7 . a. ≈ 0

8 . b. The values for x are: {1, 2, 3,..., 14}

9 . c. 0.9417.

10 . d. binomial

11 . d. 8.7

12 . a. –1.96

13 . a. 0.6321

14 . d. 360

15 . b. N ( 72 , 72 50 )

16 . a. 3 9

17 . d.

18 . b. 5.5

19 . d. 6.92

20 . a. 5

21 . b. 0.8541

22 . b. 0.2

23 . a. –1.

24 . c. matched pairs, dependent groups.

25 . d. Reject H 0 . There is sufficient evidence to conclude that there is a difference in the mean scores.

26 . c. there is sufficient evidence to conclude that the proportion for males is higher than the proportion for females.

27 . b. no

28 . b. p -value is close to 1.

29 . b. No

30 . c. y ^ = 79.96 x – 0.0094

31 . d. We should not be estimating here.

32 . a.

33 . a. The p -value is>0.10. There is insufficient information to conclude that the distribution is not uniform.

34 . c. The test is to determine if the different groups have the same means.

Questions & Answers

If X is a Uniform random variable in [ -2, 2 ], find the pdf of Y X  and E Y[ ].
Kezang Reply
I want to know statistics
Okosa Reply
why is data so important in statistics
Trixie Reply
want summary statistic on gender, age group, weight, and weight loss
are you asking question or looking for Solution
solution pls
1st convert gender and group to factor than use summary function It will give mean median and mode with other details
its a bit complicated could u bring it to my level of under standing
u know the question was put in a tabular form where we were to find the variable type, summary statistics and graph type of the given variables that's the gender,age group, weight and weight loss
if you see, gender and group are not numerical due to which they will not give you correct statistics
how you denote gender m or f
or t
ok tnk u
these are not numerical so you have to convert they as f=1; m=2; t=3 same thing you have to do with group or any variable which is character else you should drop them
from your calculation
oh OK tnk u
so pls why is data important in statistics
not only data correct data is imp
statistics works on data only
without data you can not summarize, can not predict future, can not establish relationship between two and more variables, can not prepare reports and make decisions on it
so I'll give example. suppose you want to open a restaurant and you have to choose one best location out of 5. then how you will decide which location is best for you
awww thank you pls
pls I want a brief note on observation, survey and experimentation way of obtaining data
please Tell me difference parameters and non parameter
can you tell me about the scopes of statistics?
plzzz answer me anyone .
Methods of Collecting Data Observation Observational studies allow researchers to document behavior in a natural setting and witness events that could not be produced in a lab.
Key Points Observation differs from most other forms of data collection in that the researcher does not manipulate variables or directly question participants. The advantages of observation include observing natural behavior, refining hypotheses, and allowing for observation of behavior that canno
 be produced in an artificial environment for ethical or practical reasons. The disadvantages of observation are that these studies do not produce quantitative data, do not allow for cause and effect statements, may be very time consuming, and can be prone to researcher bias.
Key Terms observational research: Research focusing on the observation of behavior outside of a laboratory setting. external validity: In research, whether or not study findings can be generalized to real world scenarios.
Surveys and Interviews Surveys are a low-cost option for gathering a large amount of data, but they are also susceptible to reporting bias.
Key Points The survey method of data collection is likely the most common of the four major research methods. The benefits of this method include low cost, large sample size, and efficiency.
The major problem with this method is accuracy: since surveys depend on subjects’ motivation, honesty, memory, and ability to respond, they are very susceptible to bias. A researcher must have a strong understanding of how to properly frame survey questions in order to gather reliable and relevant
Key Terms reliability: The degree to which a measure is likely to yield consistent results each time it is used. validity: The degree to which a measure is actually assessing the concept it was designed to measure. survey: A method for collecting qualitative and quantitative information about ind
individuals in a population.
Interviews Interviews are a type of qualitative data in which the researcher asks questions to elicit facts or statements from the interviewee. Interviews used for research can take several forms:
Informal Interview: A more conversational type of interview, no questions are asked and the interviewee is allowed to talk freely. General interview guide approach: Ensures that the same general areas of information are collected from each interviewee. Provides more focus than the conversational ap
approach, but still allows a degree of freedom and adaptability in getting the information from the interviewee. Standardized, open-ended interview: The same open-ended questions are asked to all interviewees. This approach facilitates faster interviews that can be more easily analyzed and compared
Closed, fixed-response interview (Structured): All interviewees are asked the same questions and asked to choose answers from among the same set of alternatives.
experiments An experiment involves the creation of a contrived situation in order that the researcher can manipulate one or more variables whilst controlling all of the others and measuring the resultant effects.
Boyd and Westfall1 have defined experimentation as: "...that research process in which one or more variables are manipulated under conditions which permit the collection of data which show the effects, if any, in unconfused fashion."
Experiments can be conducted either in the field or in a laboratory setting. When operating within a laboratory environment, the researcher has direct control over most, if not all, of the variables that could impact upon the outcome of the experiment
When experiments are conducted within a natural setting then they are termed field experiments. The variety test carried out by United Fruits on their Gros Michel and Valery bananas is an example of a field experiment.
parameter Parameters are factors or limits which affect the way that something can be done or made
Minhal didny get your question, can you please elaborate more
pls can u use mean n mode at the statistical summary pls
yes, statistical summary itself gives all value
but u didn't tell me the advantage and disadvantage of the experimental method
but you didn't tell me the advantage and disadvantage of experimental method
by using a sampling distribution? how to estimate the population mean using a ramdom variable n?
Jade Reply
The “average increase” for all NASDAQ stocks is the:
da Reply
any video any proof...what is point of estimation in statistics
Younis Reply
Define the meaning of statistics
Robert Reply
roductory Statistics is intended for the one-semester introduction to statistics course for students who are not mathematics or engineering majors. It focuses on the interpretation of statistical results, especially in real world settings, and assumes that students have an understanding of intermedi
statistics is science collection of method planning experiment then organizing summarizing presenting analyzing and drawing conclusion.
uses and miss uses of statistics
Identify the population, sample, parameter, statistic, variable, and data for this example. population sample parameter statistic variable data
kinds of probability samples and there advantage
Hajira Reply
are you going to explain it.
Sampling takes on two forms in statistics: probability sampling and non-probability sampling: Probability sampling uses random sampling techniques to create a sample. Non-probability samplingtechniques use non-random processes like researcher judgment or convenience sampling.
Advantages Cluster sampling: convenience and ease of use. Simple random sampling: creates samples that are highly representative of the population. Stratified random sampling: creates strata or layers that are highly representative of strata or layers in the population. Systematic sampling: creates
any example plz?
Plz write the uses and miss uses of statistical theory
what is the difference between weighted simple price index (WSPI ) & Laspeyre's Price Index ( LPI )
Basil Reply
What are the 5 steps of hypothesis testing?
Sixolisiwe Reply
5 steps of hypothesis testing
Make guesses (e.g., customers will leave if we raise our rates) State the null H0 and alternative H1 hypotheses (e.g., H0: there is no correlation) and alpha Select the sampling distribution and specify the test statistic Compute the test statistic Make a decision and interpret the results
.Five Steps in Hypothesis Testing: 1_Specify the Null Hypothesis. 2_Specify the Alternative Hypothesis. 3_Set the Significance Level (a) 4_Calculate the Test Statistic and Corresponding P-Value. 5_Drawing a Conclusion.
.Econometric Results uses Multiple Regression for the basis of looking at number of casual factors (independent χ Variables) such as Employment, being Female etc., to test for any relationship with the dependent γ Variable Wages, in order to find any evidence to support the Alternative Hypothesis(Ha
.Alternative Hypothesis (H1 or Ha) of Wage Differentials or in the extreme case, if the strength of relationship is strong enough between the dependent γ Variable, and multiple χ Variables, suggesting evidence for the Null Hypothesis ( Ho) that Wage Discrimination may exist.
.The Significance Level which is also the Critical Value gives the maximum allowable probability of making a Type I error – the Significance Level value of which is decided upon before the data sample is collected and analysed, as a guide to avoid or control making a Type I error.
Type I Error occurs when the Null Hypothesis (Ho) is not accepted when in reality the Null Hypothesis is true. A Type II Error however, occurs when one fails to reject the Null Hypothesis when in reality, the Null Hypothesis (Ho) is not true.
.The #P-Value measures the likelihood of getting the sample results if the Null Hypothesis were true, and could be defined as the smallest level of significance (observed level of significance) at which the Null Hypothesis will be rejected, assuming the Null Hypothesis (Ho) is true.
.In most cases, the research attempt is to find support for the Alternative Hypothesis (Ha or H1). Thus, the smaller the P-Value, the more the (the father out the #Test-Statistics is on the Standard Normal Distribution Diagram, and the more confident the researcher can be about rejecting the Null H
.#Test-Statistics is on the Standard Normal Distribution Diagram, and the more confident the researcher can be about rejecting the Null Hypothesis (Ho) in support for the Alternative Hypothesis (H1 / Ha).
.The #P-Value is less than the Critical Values (Significance Level) of 1% (0.01), 5% (0.05), and 10% (0.10) given in Table (1) in the Appendix, means the Null Hypothesis (Ho) that there is Wage Discrimination is not reflective of the population or equal to the Mean of the Population
.Mean of the Population(data sample of Sample Mean distribution of the Population ) which confirms that the Researcher Rejects the Null Hypothesis (Ho) and Accepts the (Alternative Hypothesis).
.See ISBN 1537512757 ; link : https://smile.amazon.co.uk/Winston-Chellie-Economics-TheBachelor-questions/dp/1537512757/ref=mp_s_a_1_1?keywords=Rachel+Adeniji&qid=1572318698&sr=8-1
see publication ' Winston and Chellie by Rachel Adeniji '
correction, dependent x variables such as Employment, being Female; dependent y variable Wages
correction, Wage Differentials such as Employment, Region affecting Wages; Wage Discrimination such as being Female or Ethnicity affecting Wages
correction_, linear regression/equation is computed as y=mx + c or y=m • x1+x2+x3+c where independent x variables eg Employment x1, Female x2 , Ethnicity x3, and dependent y variable Wages
how do you draw a line of best fit?
Josh Reply
informal explanation:lets suppose you have 10 points and you want a line to best fit on all of them. all you need to keep in mind that the distance and error should be minimum and you will get the best fit line.
how was the data collected to draw the graph
draw a straight line through the points on the graph that are most clustered with other data / points
suppose that 30% of the employees in a large factory of smokers what is the probability that there will be exactly two smokers in a randomly-chosen five-person workgroup
rayhaanah Reply
binomialPdf(5, .3, 2) .3087
are the fraction integers
Amir Reply
The ratio of male to female nurses is 2:3 or 2/3. There are 40 nurses in the ward. For every 5 nurses, how many male and female nurses are there? How many groups can be divided into shifts. Pls show the solution and explain.
DokBads Reply
in a group of 5, the probability tbat exactly 3 of the nurses are male is .6630 or 66% calculation P(X=0)+(...)+P(X=3)=.6630
i dont think u got a correct answer. you are computing for the probability not the ratio and proportion
(2+5)/40*2 = male , (2+5)/40*3 = female
40/(2+3)*2 = male , 40/(2+3)*3=female, ....sorry correction
thank you so much for the help
if x is a continuous random variable and` c` is a constant then p(x=c)
Neha Reply
the length of human pregnancies from conception to birth approximates a normal distribution with a mean of 266days and a standard deviation of 16days.(i) what length of time marks the shortest 10%of all pregnancies ?
27.6390625 days
how can I solve a Hypothetic problem that provide sample data such as 45,3_,45,28,17 ect...what is the first step
find the mean and standard deviation first
how can I get line of best fit?

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Source:  OpenStax, Introductory statistics. OpenStax CNX. May 06, 2016 Download for free at http://legacy.cnx.org/content/col11562/1.18
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