QNT 561 Week 2 Weekly Learning Assessments - Score more in the weakly learning assignments by getting instant professional help from our learned experts.
This document contains several statistics exercises involving calculating point estimates, confidence intervals, and other inferential statistics concepts. The exercises provide sample data and ask the reader to calculate things like means, variances, standard errors, and confidence intervals. They cover topics like using sample data to estimate properties of populations, constructing confidence intervals for means and proportions, and applying these statistical techniques to real-world scenarios.
This document outlines key concepts for constructing confidence intervals for a population mean when sample sizes are large or small. It discusses how to find point estimates and margins of error, and how to construct confidence intervals using z-scores or t-statistics depending on sample size. Examples are provided to demonstrate how to calculate critical values, margins of error, and minimum sample sizes needed to estimate population means within a given level of confidence.
This document outlines how to perform a chi-square test of independence using a contingency table. It explains that a contingency table displays the observed frequencies of two variables arranged in rows and columns. Expected frequencies are calculated for each cell assuming independence by multiplying the corresponding row and column totals and dividing by the sample size. A chi-square test can then determine if the observed frequencies differ significantly from the expected frequencies under independence.
This document section provides an overview of correlation and linear regression analysis. It defines correlation as a relationship between two variables and discusses different types of correlation including positive, negative, nonlinear, and no correlation. Key concepts covered include the correlation coefficient, which measures the strength and direction of linear relationships, and how to calculate and interpret the coefficient. The section also explains how to test if a population correlation is statistically significant using sample data and correlation coefficient values with tables. Examples are provided to demonstrate these techniques.
Quantitative Methods for Lawyers - Class #15 - R Boot Camp - Part 2 - Profess...Daniel Katz
This document provides an overview of statistical tests and calculations using R. It discusses loading and cleaning a dataset, doing basic calculations, and running statistical tests like the binomial distribution, normal distribution, hypothesis testing, chi-squared test, and F test. Examples are provided for each type of analysis, including the R code and interpretation. The goal is to demonstrate how to use R to analyze datasets and evaluate various statistical hypotheses.
This document outlines how to perform hypothesis tests to compare the means of two independent samples. It discusses using a two-sample z-test when samples are large and normally distributed, and a two-sample t-test when samples are small. The key steps are to state the null and alternative hypotheses, calculate the test statistic, find the critical value, make a decision to reject or fail to reject the null hypothesis, and interpret the results. Examples are provided to demonstrate these tests.
This document contains self-check exercises and applications related to hypothesis testing. It includes:
1) Multiple choice and short answer questions about hypothesis testing concepts such as standard errors, Type I and Type II errors, and determining appropriate tests.
2) Several word problems presenting hypotheses to test, sample data, and questions about determining if hypotheses can be rejected. Problems cover topics like product reliability, sales amounts, and price differences.
3) Questions about computing the power of hypothesis tests using data from previous problems.
The document covers fundamental concepts of hypothesis testing as well as applying those concepts to analyze various business and research examples.
This document contains several statistics exercises involving calculating point estimates, confidence intervals, and other inferential statistics concepts. The exercises provide sample data and ask the reader to calculate things like means, variances, standard errors, and confidence intervals. They cover topics like using sample data to estimate properties of populations, constructing confidence intervals for means and proportions, and applying these statistical techniques to real-world scenarios.
This document outlines key concepts for constructing confidence intervals for a population mean when sample sizes are large or small. It discusses how to find point estimates and margins of error, and how to construct confidence intervals using z-scores or t-statistics depending on sample size. Examples are provided to demonstrate how to calculate critical values, margins of error, and minimum sample sizes needed to estimate population means within a given level of confidence.
This document outlines how to perform a chi-square test of independence using a contingency table. It explains that a contingency table displays the observed frequencies of two variables arranged in rows and columns. Expected frequencies are calculated for each cell assuming independence by multiplying the corresponding row and column totals and dividing by the sample size. A chi-square test can then determine if the observed frequencies differ significantly from the expected frequencies under independence.
This document section provides an overview of correlation and linear regression analysis. It defines correlation as a relationship between two variables and discusses different types of correlation including positive, negative, nonlinear, and no correlation. Key concepts covered include the correlation coefficient, which measures the strength and direction of linear relationships, and how to calculate and interpret the coefficient. The section also explains how to test if a population correlation is statistically significant using sample data and correlation coefficient values with tables. Examples are provided to demonstrate these techniques.
Quantitative Methods for Lawyers - Class #15 - R Boot Camp - Part 2 - Profess...Daniel Katz
This document provides an overview of statistical tests and calculations using R. It discusses loading and cleaning a dataset, doing basic calculations, and running statistical tests like the binomial distribution, normal distribution, hypothesis testing, chi-squared test, and F test. Examples are provided for each type of analysis, including the R code and interpretation. The goal is to demonstrate how to use R to analyze datasets and evaluate various statistical hypotheses.
This document outlines how to perform hypothesis tests to compare the means of two independent samples. It discusses using a two-sample z-test when samples are large and normally distributed, and a two-sample t-test when samples are small. The key steps are to state the null and alternative hypotheses, calculate the test statistic, find the critical value, make a decision to reject or fail to reject the null hypothesis, and interpret the results. Examples are provided to demonstrate these tests.
This document contains self-check exercises and applications related to hypothesis testing. It includes:
1) Multiple choice and short answer questions about hypothesis testing concepts such as standard errors, Type I and Type II errors, and determining appropriate tests.
2) Several word problems presenting hypotheses to test, sample data, and questions about determining if hypotheses can be rejected. Problems cover topics like product reliability, sales amounts, and price differences.
3) Questions about computing the power of hypothesis tests using data from previous problems.
The document covers fundamental concepts of hypothesis testing as well as applying those concepts to analyze various business and research examples.
QNT Weekly learning assessments - Questions and Answers | UOP E AssignmentsUOP E Assignments
What the benefits of learning QNT 561 Weekly Learning Assessments ? Know from UOP E Assignments which is the largest going online educational portal whose motive is to provide best knowledge to UOP students for final exam. You get QNT 561 weekly learning assessments question and answers, QNT 561 weekly learning assessments 30 questions, QNT 561 weekly learning assessments quiz 1 answers etc in USA.
http://www.uopeassignments.com/university-of-phoenix/QNT-561/Weekly-Learning-Assessments.html
This document outlines key concepts related to discrete and continuous random variables including:
- Discrete random variables can take countable values while continuous can take any value in an interval.
- The probability distribution of a discrete random variable lists all possible values and their probabilities.
- Key metrics for discrete variables include the mean, which is the expected value, and standard deviation, which measures spread.
- The cumulative distribution function provides the probability that a random variable is less than or equal to a given value.
This document contains 54 multiple choice questions about probability concepts from the textbook "Quantitative Analysis for Management, 11e". The questions cover topics such as fundamental probability concepts, mutually exclusive and collectively exhaustive events, statistically independent events, probability distributions including binomial and normal distributions, and Bayes' theorem. For each question, the answer and difficulty level is provided along with the topic area.
This document contains examples and explanations of key concepts related to the normal distribution and probability, including:
- Calculating probabilities for various z-scores under the standard normal distribution
- Using the normal distribution to find probabilities for real-world scenarios involving cassette deck lifetimes, cornflake weights, and CEO ages
- Properties of the sampling distribution of sample means, including how it approaches normality as sample size increases based on the Central Limit Theorem
- Worked examples applying concepts like finding probabilities and cutoff scores for sample means and binomial experiments
This document provides an overview of key concepts regarding normal distributions, including:
- Normal distributions have properties such as being bell-shaped and symmetric about the mean. The mean, median and mode are equal for a normal distribution.
- The standard normal distribution has a mean of 0 and standard deviation of 1. Any normally distributed value can be converted to a z-score and related to the standard normal distribution.
- Areas under the normal curve can be used to find probabilities for normally distributed variables. Specific examples are provided to demonstrate finding probabilities and related values.
This document provides an overview of key concepts in descriptive statistics including:
- Parameters describe populations while statistics describe samples
- Measures of central tendency include the mean, median, and mode
- Measures of variation/dispersion include range, variance, standard deviation, and coefficient of variation
- The empirical rule and Chebyshev's theorem describe how data is distributed around the mean
- Z-scores and percentiles relate individual values to the overall distribution
This document provides solutions to practice problems for hypothesis testing. It tests claims about population parameters such as drug failure rates and textbook prices against sample data. For each problem it states the null and alternative hypotheses, calculates the test statistic, finds the critical value, and makes a decision to reject or fail to reject the null hypothesis. It defines type I and type II errors and explains how lower variation in test scores does not necessarily indicate students are performing better.
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 8: Hypothesis Testing
8.2: Testing a Claim About a Proportion
This document contains examples and explanations of key concepts related to the normal distribution and probability, including:
- Calculating probabilities for various z-scores under the standard normal distribution
- Using the normal distribution to find probabilities for real-world scenarios involving cassette deck lifetimes, cornflake weights, and CEO ages
- Properties of the sampling distribution of sample means, including how it approaches normality as sample size increases based on the Central Limit Theorem
- Worked examples applying concepts like finding probabilities and cutoff scores for sample means and binomial experiments
This document provides an overview of estimation and confidence intervals. It defines key terms like point estimates, confidence intervals, and level of confidence. It discusses how to construct confidence intervals for population means when the standard deviation is known or unknown. It also covers how to construct confidence intervals for population proportions. Examples are provided to illustrate how to calculate confidence intervals and interpret the results. Factors that affect the width of confidence intervals like sample size, population variability, and confidence level are also explained.
The document discusses various methods for constructing interval estimates from sample data to describe the range of values within which the unknown population parameter is likely to fall. It provides examples of how to calculate confidence intervals for means, proportions, and percentages using information about the sample size, mean, standard deviation, and desired confidence level. Formulas for the standard error and t-distribution are also presented when the population standard deviation is unknown.
- The document provides an overview of topics that may be covered on the Math 533 final exam, including hypothesis testing, the binomial distribution, descriptive statistics, confidence intervals, and regression analysis.
- It includes examples of sample questions and worked problems for each topic to help students prepare.
This document contains multiple statistics exercises involving chi-square tests of goodness of fit and independence. It includes examples of contingency tables with observed and expected frequencies, calculations of chi-square test statistics, and statements of null and alternative hypotheses. Students are asked to perform chi-square analyses to determine if data follow particular distributions or if two variables are independent. The exercises cover concepts like degrees of freedom, contingency tables, chi-square distributions, and testing hypotheses with chi-square tests.
This document contains 5 questions and their answers. Question 1 analyzes survey data to determine if more than 61% of people sleep 7 or more hours per night on weekends. Question 2 calculates a p-value for a hypothesis test comparing the means of two employment tests. Question 3 performs a hypothesis test to examine if a sample's mean score differs from the expected population mean. Question 4 uses a chi-squared test to determine if there is a preference for certain class times. Question 5 provides commute data and asks to calculate the line of best fit, confidence intervals, and determine if distance can indicate travel time.
Quantitative Analysis For Management 11th Edition Render Test BankRichmondere
Full download : http://alibabadownload.com/product/quantitative-analysis-for-management-11th-edition-render-test-bank/ Quantitative Analysis For Management 11th Edition Render Test Bank
Random Variable
Discrete Probability Distribution
continuous Probability Distribution
Probability Mass Function
Probability Density Function
Expected value
variance
Binomial Distribution
poisson distribution
normal distribution
This document provides instructions for Assessment Item 3 of the PRBE002 unit, which involves solving a set of problems using statistical and decision-making techniques. It includes 5 questions related to analyzing data and testing hypotheses using statistical methods. Students are asked to show their work and calculations clearly and explain their answers fully. Their responses will be assessed based on properly applying statistical techniques and making informed decisions based on the analysis.
The director of admissions at Kinzua University in Nova Scotia est.docxmehek4
The document provides information about admissions data from Kinzua University. It gives the estimated distribution of admissions based on past experience, with probabilities and expected admission numbers. It then asks to compute the expected number of admissions, variance, and standard deviation. The next section provides information about a sample of tax returns regarding charitable contributions and the probability of audited returns having certain deductions.
This document contains a 15-question review worksheet covering chapters 7-8 on probability distributions including binomial, normal, and other discrete random variables. The questions test concepts such as identifying appropriate probability distributions based on a scenario, calculating probabilities and other values using distribution formulas, interpreting probabilities and other statistical measures, and assumptions when working with random variables. The answers to each question are also provided.
QNT Weekly learning assessments - Questions and Answers | UOP E AssignmentsUOP E Assignments
What the benefits of learning QNT 561 Weekly Learning Assessments ? Know from UOP E Assignments which is the largest going online educational portal whose motive is to provide best knowledge to UOP students for final exam. You get QNT 561 weekly learning assessments question and answers, QNT 561 weekly learning assessments 30 questions, QNT 561 weekly learning assessments quiz 1 answers etc in USA.
http://www.uopeassignments.com/university-of-phoenix/QNT-561/Weekly-Learning-Assessments.html
This document outlines key concepts related to discrete and continuous random variables including:
- Discrete random variables can take countable values while continuous can take any value in an interval.
- The probability distribution of a discrete random variable lists all possible values and their probabilities.
- Key metrics for discrete variables include the mean, which is the expected value, and standard deviation, which measures spread.
- The cumulative distribution function provides the probability that a random variable is less than or equal to a given value.
This document contains 54 multiple choice questions about probability concepts from the textbook "Quantitative Analysis for Management, 11e". The questions cover topics such as fundamental probability concepts, mutually exclusive and collectively exhaustive events, statistically independent events, probability distributions including binomial and normal distributions, and Bayes' theorem. For each question, the answer and difficulty level is provided along with the topic area.
This document contains examples and explanations of key concepts related to the normal distribution and probability, including:
- Calculating probabilities for various z-scores under the standard normal distribution
- Using the normal distribution to find probabilities for real-world scenarios involving cassette deck lifetimes, cornflake weights, and CEO ages
- Properties of the sampling distribution of sample means, including how it approaches normality as sample size increases based on the Central Limit Theorem
- Worked examples applying concepts like finding probabilities and cutoff scores for sample means and binomial experiments
This document provides an overview of key concepts regarding normal distributions, including:
- Normal distributions have properties such as being bell-shaped and symmetric about the mean. The mean, median and mode are equal for a normal distribution.
- The standard normal distribution has a mean of 0 and standard deviation of 1. Any normally distributed value can be converted to a z-score and related to the standard normal distribution.
- Areas under the normal curve can be used to find probabilities for normally distributed variables. Specific examples are provided to demonstrate finding probabilities and related values.
This document provides an overview of key concepts in descriptive statistics including:
- Parameters describe populations while statistics describe samples
- Measures of central tendency include the mean, median, and mode
- Measures of variation/dispersion include range, variance, standard deviation, and coefficient of variation
- The empirical rule and Chebyshev's theorem describe how data is distributed around the mean
- Z-scores and percentiles relate individual values to the overall distribution
This document provides solutions to practice problems for hypothesis testing. It tests claims about population parameters such as drug failure rates and textbook prices against sample data. For each problem it states the null and alternative hypotheses, calculates the test statistic, finds the critical value, and makes a decision to reject or fail to reject the null hypothesis. It defines type I and type II errors and explains how lower variation in test scores does not necessarily indicate students are performing better.
Please Subscribe to this Channel for more solutions and lectures
http://www.youtube.com/onlineteaching
Chapter 8: Hypothesis Testing
8.2: Testing a Claim About a Proportion
This document contains examples and explanations of key concepts related to the normal distribution and probability, including:
- Calculating probabilities for various z-scores under the standard normal distribution
- Using the normal distribution to find probabilities for real-world scenarios involving cassette deck lifetimes, cornflake weights, and CEO ages
- Properties of the sampling distribution of sample means, including how it approaches normality as sample size increases based on the Central Limit Theorem
- Worked examples applying concepts like finding probabilities and cutoff scores for sample means and binomial experiments
This document provides an overview of estimation and confidence intervals. It defines key terms like point estimates, confidence intervals, and level of confidence. It discusses how to construct confidence intervals for population means when the standard deviation is known or unknown. It also covers how to construct confidence intervals for population proportions. Examples are provided to illustrate how to calculate confidence intervals and interpret the results. Factors that affect the width of confidence intervals like sample size, population variability, and confidence level are also explained.
The document discusses various methods for constructing interval estimates from sample data to describe the range of values within which the unknown population parameter is likely to fall. It provides examples of how to calculate confidence intervals for means, proportions, and percentages using information about the sample size, mean, standard deviation, and desired confidence level. Formulas for the standard error and t-distribution are also presented when the population standard deviation is unknown.
- The document provides an overview of topics that may be covered on the Math 533 final exam, including hypothesis testing, the binomial distribution, descriptive statistics, confidence intervals, and regression analysis.
- It includes examples of sample questions and worked problems for each topic to help students prepare.
This document contains multiple statistics exercises involving chi-square tests of goodness of fit and independence. It includes examples of contingency tables with observed and expected frequencies, calculations of chi-square test statistics, and statements of null and alternative hypotheses. Students are asked to perform chi-square analyses to determine if data follow particular distributions or if two variables are independent. The exercises cover concepts like degrees of freedom, contingency tables, chi-square distributions, and testing hypotheses with chi-square tests.
This document contains 5 questions and their answers. Question 1 analyzes survey data to determine if more than 61% of people sleep 7 or more hours per night on weekends. Question 2 calculates a p-value for a hypothesis test comparing the means of two employment tests. Question 3 performs a hypothesis test to examine if a sample's mean score differs from the expected population mean. Question 4 uses a chi-squared test to determine if there is a preference for certain class times. Question 5 provides commute data and asks to calculate the line of best fit, confidence intervals, and determine if distance can indicate travel time.
Quantitative Analysis For Management 11th Edition Render Test BankRichmondere
Full download : http://alibabadownload.com/product/quantitative-analysis-for-management-11th-edition-render-test-bank/ Quantitative Analysis For Management 11th Edition Render Test Bank
Random Variable
Discrete Probability Distribution
continuous Probability Distribution
Probability Mass Function
Probability Density Function
Expected value
variance
Binomial Distribution
poisson distribution
normal distribution
This document provides instructions for Assessment Item 3 of the PRBE002 unit, which involves solving a set of problems using statistical and decision-making techniques. It includes 5 questions related to analyzing data and testing hypotheses using statistical methods. Students are asked to show their work and calculations clearly and explain their answers fully. Their responses will be assessed based on properly applying statistical techniques and making informed decisions based on the analysis.
The director of admissions at Kinzua University in Nova Scotia est.docxmehek4
The document provides information about admissions data from Kinzua University. It gives the estimated distribution of admissions based on past experience, with probabilities and expected admission numbers. It then asks to compute the expected number of admissions, variance, and standard deviation. The next section provides information about a sample of tax returns regarding charitable contributions and the probability of audited returns having certain deductions.
This document contains a 15-question review worksheet covering chapters 7-8 on probability distributions including binomial, normal, and other discrete random variables. The questions test concepts such as identifying appropriate probability distributions based on a scenario, calculating probabilities and other values using distribution formulas, interpreting probabilities and other statistical measures, and assumptions when working with random variables. The answers to each question are also provided.
1.value3.68 pointsExercise 5-91Nineteen percent of all .docxhyacinthshackley2629
Juanita is the new HR manager at a nonprofit organization that provides food assistance. In initial meetings, her boss Rich outlined many HR responsibilities but conveyed limited authority for Juanita. She wants to contribute more. Juanita learns the organization struggles with qualified staffing due to limited resources. Cash donations are down, impacting hiring. For a class project, Juanita realizes she can study the organization's compliance with equal employment opportunity laws to help improve HR practices and understand her role better.
TitleABC123 Version X1Time to Practice – Week Three .docxedwardmarivel
Title
ABC/123 Version X
1
Time to Practice – Week Three
PSYCH/625 Version 1
2
University of Phoenix Material
Time to Practice – Week Three
Complete both Part A and Part B below.
Part A
Some questions in Part A require that you access data from Statistics for People Who (Think They) Hate Statistics. This data is available on the student website under the Student Test Resources link.
1. For the following research questions, create one null hypothesis, one directional research hypothesis, and one nondirectional research hypothesis.
a. What are the effects of attention on out-of-seat classroom behavior?
Research Hypothesis: There will be a relationship between the effects of attention on out-of-seat classroom behavior versus in-seat-classroom behavior.
b. What is the relationship between the quality of a marriage and the quality of the spouses’ relationships with their siblings?
Null Hypothesis: There will be no relationship in the relationship between the quality of a marriage and the quality of the spouses’ relationship with their siblings.
c. What is the best way to treat an eating disorder?
One Directional Research Hypothesis:
2. Provide one research hypothesis and an equation for each of the following topics:
a. The amount of money spent on food among undergraduate students and undergraduate student-athletes
b. The average amount of time taken by white and brown rats to get out of a maze
c. The effects of Drug A and Drug B on a disease
d. The time to complete a task in Method 1 and Method 2
3. Why does the null hypothesis presume no relationship between variables?
4. Create a research hypothesis tested using a one-tailed test and a research hypothesis tested using a two-tailed test.
5. What does the critical value represent?
6. Given the following information, would your decision be to reject or fail to reject the null hypothesis? Setting the level of significance at .05 for decision making, provide an explanation for your conclusion.
a. The null hypothesis that there is no relationship between the type of music a person listens to and his crime rate (p < .05).
In Hypothesis Testing, we typically deem a research hypothesis to be significant, if the odds of two means actually being equal are no greater than 1 in 20 or .05 (5%) or less.
b. The null hypothesis that there is no relationship between the amount of coffee consumption and GPA (p = .62).
c. The null hypothesis that there is a negative relationship between the number of hours worked and level of job satisfaction (p = .51).
7. Why is it harder to find a significant outcome (all other things being equal) when the research hypothesis is being tested at the .01 rather than the .05 level of significance?
At the .01 level, there is less room for error because the test is more rigorous.
8. Why should we think in terms of “failing to reject” the null rather than just accepting it?
9. When is it appropriate to use the one-sample z test?
10. What similarity does a z test have ...
InstructionDue Date 6 pm on October 28 (Wed)Part IProbability a.docxdirkrplav
This document discusses implementing a social, environmental, and economic impact measurement system within a company. It explains that measuring sustainability performance is critical for evaluating projects, the company, and its members. A proper measurement system allows companies to develop a sustainability strategy, allocate resources to support it, and evaluate trade-offs between sustainability projects. The document provides examples from Nike and P&G of measuring impacts to demonstrate the business case for sustainability. It stresses that measurement is important for linking performance to sustainability principles and facilitating continuous improvement.
Name ______________________________Signature ______________________.docxrosemarybdodson23141
This document contains instructions for a midterm exam in a quantitative analysis class. Students are allowed to use notes and calculators, and must show all work. The exam contains 5 problems worth 25 points each, but students only need to complete 4 problems. Questions involve probability, hypothesis testing, regression, and confidence intervals related to business scenarios.
1.A local restaurant is committed to providing its patr.docxjoyjonna282
1.
A local restaurant is committed to providing its patrons with the best dining experience possible. On a recent survey, the restaurant asked patrons to rate the quality of their entrées. The responses ranged from 1 to 5, where 1 indicated a disappointing entrée and 5 indicated an exceptional entrée.
The results of the survey are as follows:
2 5 1 5 1 5 4 3 3 3 1 2
1 2 2 3 1 4 4 1 2 3 1 1
4 5 1 1 1 3 1 2 1 4 2 2
PictureClick here for the Excel Data File
a.
Construct frequency and relative frequency distributions that summarize the survey’s results. (Do not round intermediate calculations. Round "relative frequency" to 3 decimal places.)
Rating Frequency Relative
Frequency
5
4
3
2
1
Total
b.
Are patrons generally satisfied with the quality of their entrées?
No
Yes
rev: 07_05_2013_QC_32367, 03_04_2014_QC_44527
2.
Consider the following data set:
1 10 5 6 8 8 10 12 15 12
8 11 8 4 3 9 12 3 10 8
8 12 4 4 4 12 10 6 11 6
7 -6 31 16 -3 9 13 6 5 -4
29 -3 5 3 24 24 10 23 32 2
-5 -4 -2 14 -2 35 26 10 18 28
5 3 -6 7 28 36 16 3 -4 5
a-1. Construct a frequency distribution using classes of −10 up to 0, 0 up to 10, etc.
Classes Frequency
–10 up to 0
0 up to 10
10 up to 20
20 up to 30
30 up to 40
Total
a-2. How many of the observations are at least 10 but less than 20?
Number of observations
b-1.
Construct a relative frequency distribution and a cumulative relative frequency distribution. (Round "relative frequency" and "cumulative relative frequency" to 3 decimal places.)
Class Relative
Frequency Cumulative
Relative Frequency
–10 up to 0
0 up to 10
10 up to 20
20 up to 30
30 up to 40
Total
b-2.
What percent of the observations are at least 10 but less than 20? (Round your answer to 1 decimal place.)
Percent of observations %
b-3. What percent of the observations are less than 20? (Round your answer to 1 decimal place.)
Percent of observations %
c. Is the distribution symmetric? If not, then how is it skewed?
Not symmetric, skewed to right
Symmetric or Skewed to left
rev: 07_05_2013_QC_32367
3.
Assume that X is a binomial random variable with n = 16 and p = 0.66. Calculate the following probabilities. (Round your intermediate and final answers to 4 decimal places.)
a. P(X = 15)
b. P(X = 14)
c. P(X ≥ 14)
rev: 04_26_2013_QC_29765; rev: 08_07_20
4.
A professor of management has heard that twelve students in his class of 52 have landed an internship for the summer. Suppose he runs into two of his students in the corridor.
a.
Find the probability that neither of these students has landed an internship. (Round your intermediate calculations and final answer to 4 decimal places.)
formula176.mml
b.
Find the probability that both of these students h ...
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QNT 561 Final Exam Guide (New, 2017)
QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions (Financial Data)
QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions (Consumer Food)
QNT 561 Week 2 Case Study MBA Schools in Asia Pacific (2 Papers)
QNT 561 Week 3 Case Study SuperFun Toys (2 Papers)
QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point
QNT 561 Week 4 Case the Payment Time
QNT 561 Week 5 Spicy Wings
Answer all 20 questions. Make sure your answers are as complet.docxfestockton
This document provides instructions for a 20 question statistics exam. It states that students must show all work and explanations for answers, as answers without work will not be accepted. If technology is used to calculate answers, the source and steps must be explained. Students should record their answers and work on the provided answer sheet. The exam covers topics like hypothesis testing, probability, confidence intervals, regression, and more. It requires justifying answers and showing steps for full credit.
1 Review and Practice Exam Questions for Exam 2 Lea.docxmercysuttle
1
Review and Practice Exam Questions for Exam 2
Learning Objectives:
Chapter 17: Thinking about chance
• Explain how random events behave in the short run and in the long run and how random and
haphazard are not the same thing.
• Perform basic probability calculations using die rolls and coin tosses.
• Define probability, and apply the rules for probability.
• Explain whether the law of averages is true.
• Explain how personal probability differs from a scientific or experimental probability.
Chapter 18: Probability models
• Define a probability model. Create a probability model for a particular story’s events.
• Apply the basic rules of probability to a story problem.
• Calculate probabilities using a probability model, including summing up probabilities or
subtracting probabilities from the total.
• Define a sampling distribution.
Chapter 20: The house edge: expected values
• Define expected value, and calculate the expected value when given a probability model.
• Define the law of large numbers, and explain how it is different from the mythical “law of
averages.”
• Explain how casinos and insurance companies stay in business and make money.
Chapter 13: The Normal distribution
• Identify data that is Normally distributed.
• Discuss how the shape/position of the Normal curve changes when the standard deviation
increases/decreases or when the mean increases/decreases.
• Define the standardized value or Z-score. Calculate the Z-score, and use the Z-score to do
comparisons.
• Calculate probabilities and cut-off values using the 68%-95%-99.7% (Empirical) Rule.
• Identify the mean, standard deviation, cut-off value, probability, and Z-score on a Normal curve.
• Use the Normal table to get percentiles (probabilities) for forward problems and to get Z-scores
in order to determine cut-offs for backward problems using both > and < in the inequalities.
• Recognize whether a story is a forward or backward Normal distribution problem, and perform
the appropriate calculations showing correct notation, the initial probability expression, and all
necessary steps.
2
Chapter 21: What is a confidence interval?
• Define statistical inference and explain when statistical inference is used.
• Explain what the confidence interval means and whether the results refer to the population or
the sample.
• Calculate the margin of error and identify the margin of error in a confidence statement.
Explain what type of error is covered in the margin of error.
• Determine whether a story is better described with a proportion or a mean.
• Use appropriate notation for proportions and means, both in the population and the sample.
• Calculate a confidence interval for a proportion and for a mean.
• Describe how increasing/decreasing the sample size or confidence level changes the margin of
error (width of the confidence interval).
• Apply cautions for using confidence inte ...
Instructions and Advice · This assignment consists of six que.docxdirkrplav
Instructions and Advice:
· This assignment consists of six questions. They each have lots of parts but most of them are very short!
· Data for Questions 3 and 6 are in the companion Excel spreadsheet <Asst3_2013_Data.xlsx>.
· Present the parts of your answers in the same order as the questions are asked.
· Do not include any original data in your printed submission.
· Maintain all precision in your calculator or in Excel as you do your multi-step computations. Round off to fewer decimal places only when you write your work and the final answer down to hand in.
· When formatting numbers in Excel, display only as many decimal places as provide decision-making value to the reader.
Question 1 – Interpreting or Misinterpreting Correlation
a) Various factors are associated with the gross domestic product (GDP) of nations. State whether each of the following statements is reasonable or not. If not, explain the blunder.
(i) A correlation of –0.722 shows that there is almost no association between GDP and Infant Mortality Rate.
(ii) There is a correlation of 0.44 between GDP and Continent.
(iii) There is a very strong correlation of 1.22 between Life Expectancy and GDP.
(iv) The correlation between Literacy Rate and GDP was 0.83. This shows that countries wanting to increase their standard of living should invest heavily in education.
b) An article in a business magazine reported that Internet E-commerce has doubled nearly every three years. It then stated that there was a high correlation between sales made on the Internet and year. Do you think this is an appropriate summary? Explain in one sentence.
c) Simpson’s Paradox can occur in regression, when a relationship between variables within groups of observations is reversed if all the data are combined. Here is an example.
Group
X
Y
Group
X
Y
1
1
10.1
2
6
18.3
1
2
8.9
2
7
17.1
1
3
8.9
2
8
16.2
1
4
6.9
2
9
15.1
1
5
6.1
2
10
14.3
(i) Make a scatterplot of the data for Group 1 and add the least squares line. Describe the relationship between Y and X for Group 1. Find the correlation (using Excel).
(ii) Do the same for Group 2.
(iii) Make a scatterplot using all 10 observations and add the least squares line. Find the correlation (using Excel).
(iv) Summarize your findings in one or two sentences.
d) Since 1980, average mortgage interest rates in the U.S. have fluctuated from a low of under 6% to a high of over 14%. Is there a relationship between the amount of money people borrow and the interest rate that’s offered? Here is a scatterplot of Total Mortgages in the U.S. (in millions of 2005 dollars) vs. Interest Rates at various times over the past 26 years. The correlation is -0.84.
(i) Describe the relationship between Total Mortgages and Interest Rate.
(ii) If we standardized both variables, what would the correlation coefficient between the standardized variables be?
(iii) If we were to measure Total Mortgages in thousands of dollars instead of millions of dollars, how would the.
Assignment 05MA260 Statistical Analysis IDirections Be sure t.docxfredharris32
Assignment 05
MA260 Statistical Analysis I
Directions: Be sure to save an electronic copy of your answer before submitting it to Ashworth College for grading. Unless otherwise stated, answer in complete sentences, and be sure to use correct English, spelling, and grammar. Refer to the "Assignment Format" page located on the Course Home page for specific format requirements.
NOTE: Show your work in the problems.
1. Compute the mean and variance of the following discrete probability distribution.
x
P(x)
2
.50
8
.30
10
.20
2. The Computer Systems Department has eight faculty, six of whom are tenured. Dr. Vonder, the chair, wants to establish a committee of three department faculty members to review the curriculum. If she selects the committee at random:
a. What is the probability all members of the committee are tenured?
b. What is the probability that at least one member is not tenured? (Hint: For this question, use the complement rule).
3. New Process, Inc., a large mail-order supplier of women’s fashions, advertises same-day service on every order. Recently, the movement of orders has not gone as planned, and there were a large number of complaints. Bud Owens, director of customer service, has completely redone the method of order handling. The goal is to have fewer than five unfilled orders on hand at the end of 95% of the working days. Frequent checks of the unfilled orders follow a Poisson distribution with a mean of two orders. A Poisson distribution is a discrete frequency distribution.
Has New Process, Inc. lived up to its internal goal? Cite evidence.
4. Recent information published by the U.S. Environmental Protection Agency indicates that Honda is the manufacturer of four of the top nine vehicles in terms of fuel economy.
a. Determine the probability distribution for the number of Hondas in a sample of three cars chosen from the top nine.
b. What is the likelihood that in the sample of three at least one Honda is included?
Grading Rubric
Please refer to the rubric below for the grading criteria for this assignment.
CATEGORYExemplarySatisfactoryUnsatisfactoryUnacceptable
15 points11 points7 points3 points
The student provides a clear
and logical table to organize
data and accurately includes
the equations and the correct
answers for the mean and
the variance.
The student provides an
adequate table to organize
data and accurately includes
the equations and the
correct answer for either
the mean or the variance.
The student does not
provide a clear and logical
table to organize data and
accurately includes the
equations and may have
only one correct answer for
the mean or the variance.
The student does not
provide a clear and logical
table to organize data and
has only 1 accurate
equation and one correct
answer for the mean or the
variance.
20 points15 points10 points5 points
The student provides correct
equations and answers for
both parts of the question.
The student provides correct
equatio ...
FOR MORE CLASSES VISIT
www.qnt561nerd.com
QNT 561 Final Exam Guide (New, 2017)
QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions (Financial Data)
QNT 561 Week 1 Assignment Statistics Concepts and Descriptive Measures Instructions (Consumer Food)
QNT 561 Week 2 Case Study MBA Schools in Asia Pacific (2 Papers)
QNT 561 Week 3 Case Study SuperFun Toys (2 Papers)
QNT 561 Week 3 Assignment Expansion Strategy and Establishing a Re-Order Point
QNT 561 Week 4 Case the Payment Time
QNT 561 Week 5 Spicy Wings Case Study
STAT 200 Introduction to Statistics Final Examination, Spri.docxrafaelaj1
STAT 200: Introduction to Statistics
Final Examination, Spring 2019 OL3
Page 1 of 8
STAT 200
OL3 Sections
Final Exam
Spring 2019
The final exam will be posted at 12:01 am on April 19, 2019, and
it is due at 11:59 pm on April 21, 2019 Eastern Time.
This is an open-book exam. You may refer to your text and other course materials
for the current course as you work on the exam, and you may use a calculator,
applets, or Excel. You must complete the exam individually. Neither collaboration
nor consultation with others is allowed. It is a violation of the UMUC Academic
Dishonesty and Plagiarism policy to use unauthorized materials or work from
others.
Answer all 20 questions. Make sure your answers are as complete as possible,
particularly when it asks for you to show your work. Answers that come straight
from calculators, programs or software packages without any explanation will not
be accepted. If you need to use technology (for example, Excel, online or hand-
held calculators, statistical packages) to aid in your calculation, you must cite the
sources and explain how you get the results. For example, state the Excel function
along with the required parameters when using Excel; describe the detailed steps
when using a hand-held calculator; or provide the URL and detailed steps when
using an online calculator, and so on.
Record your answers and work on the separate answer sheet provided.
This exam has 20 problems; 5% for each problems.
You must include the Honor Pledge on the title page of your submitted final exam.
Exams submitted without the Honor Pledge will not be accepted.
STAT 200: Introduction to Statistics
Final Examination, Spring 2019 OL3
Page 2 of 8
1. You wish to estimate the mean cholesterol levels of patients two days after they had a heart attack. To
estimate the mean, you collect data from 28 heart patients. Justify for full credit.
(a) Which of the followings is the sample?
(i) Mean cholesterol levels of 28 patients recovering from a heart attack suffered two
days ago
(ii) Cholesterol level of the person recovering from heart attack suffered two days ago
(iii) Set of all patients recovering from a heart attack suffered two days ago
(iv) Set of 28 patients recovering from a heart attack suffered two days ago
(b) Which of the followings is the variable?
(i) Mean cholesterol levels of 28 patients recovering from a heart attack suffered two
days ago
(ii) Cholesterol level of the person recovering from heart attack suffered two days ago
(iii) Set of all patients recovering from a heart attack suffered two days ago
(iv) Set of 28 patients recovering from a heart attack suffered two days ago
2. In order to collect data on the number of courses that your classmates take in this semester, you plan
on asking them: “How many UMUC courses are you taking in this semester? “Justify for full credit.
(a) Which type of d.
1.)Two thousand frequent business travelers are asked which midwe.docxmansonagnus
1.)
Two thousand frequent business travelers are asked which midwestern city they prefer: Indianapolis, Saint Louis, Chicago, or Milwaukee. 107 liked Indianapolis best, 454 liked Saint Louis, 1370 liked Chicago, and the remainder preferred Milwaukee. Develop a frequency table and a relative frequency table to summarize this information. (Round relative frequency to 3 decimal places.)
City Frequency Relative Frequency
Indianapolis
St. Louis
Chicago
Milwaukee
2.)
In June an investor purchased 350 shares of Oracle (an information technology company) stock at $22 per share. In August she purchased an additional 420 shares at $25 per share. In November she purchased an additional 510 shares at $31 per share. What is the weighted mean price per share? (Round your answer to 2 decimal places. Omit the "$" sign in your response.)
The weighted mean is $
3.
Sally Reynolds sells real estate along the coastal area of Northern California. Below is the total amount of her commissions earned since 2000.
Year Amount (thousands)
2000 $237.51
2001 233.8
2002 206.97
2003 248.14
2004 164.69
2005 292.16
2006 269.11
2007 225.57
2008 255.33
2009 202.67
2010 206.53
Find the mean, median, and mode of the commissions she earned for the 11 years. (Round your answers to 2 decimal places.)
Mean
Median
Mode
4.The unemployment rate in the state of Alaska by month is given in the table below:
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
7.00
7.20
6.60
8.80
7.40
7.60
7.50
8.30
7.10
7.20
7.80
8.60
(a)
What is the arithmetic mean of the Alaska unemployment rates? (Round your answer to 2 decimal places.)
Arithmetic mean
(b)
Find the median and the mode for the unemployment rates. (Round your answers to 2 decimal places.)
Median
Mode
5.)
A sample of the personnel files of eight employees at the Pawnee location of Acme Carpet Cleaners, Inc., revealed that during the last six-month period they lost the following number of days due to illness:
5
5
4
4
1
2
0
6
A sample of eight employees during the same period at the Chickpee location of Acme Carpets revealed they lost the following number of days due to illness.
2
1
0
10
2
2
3
0
(a)
Calculate the range, mean and mean deviations for the Pawnee location and the Chickpee location.(Round mean and mean deviation to 2 decimal places.)
Pawnee
location Chickpee
location
Range
Mean
Mean deviation
(b-1) Based on the sample data, which location has fewer lost days?
(b-2) Based on the sample data, which location has less variation?
6.
The annual report of Dennis Industries cited these primary earnings per common share for the past 5 years:
$2.29, $1.18, $2.22, $4.42, and $3.4.
(a)
What is the arithmetic mean primary.
The document provides a review of key concepts for a statistics final exam, including how to calculate regression equations and lines, probabilities using normal and binomial distributions, hypothesis testing, and other statistical analyses. It includes examples of problems and questions that may appear on the exam.
Similar to QNT 561 Week 2 Weekly Learning Assessments – Assignment (17)
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
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ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
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1. QNT 561 Week 2 Weekly
Learning Assessments –
Assignment
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By www.uopstudents.com
2. Chapter 5 Exercise 4
A large company must hire a new president. The Board of Directors
prepares a list of five candidates, all of whom are equally qualified. Two
of these candidates are members of a minority group. To avoid bias in
the selection of the candidate, the company decides to select the
president by lottery.
a. What is the probability one of the minority candidates is hired?
(Round your answer to 1 decimal place.)
b. Which concept of probability did you use to make this estimate?
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3. Chapter 5 Exercise 14
The chair of the board of directors says, "There is a 50% chance this
company will earn a profit, a 30% chance it will break even, and a 20%
chance it will lose money next quarter."
a. Use an addition rule to find the probability the company will not lose
money next quarter. (Round your answer to 2 decimal places.)
b. Use the complement rule to find the probability it will not lose
money next quarter. (Round your answer to 2 decimal places.)
Find the Weekly Learning Assessment answers here
QNT 561 Week 2 Weekly Learning Assessments
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4. Chapter 5 Exercise 22
A National Park Service survey of visitors to the Rocky Mountain region
revealed that 50% visit Yellowstone Park, 40% visit the Tetons, and 35%
visit both.
a. What is the probability a vacationer will visit at least one of these
attractions? (Round your answer to 2 decimal places.)
b. What is the probability .35 called?
c. Are the events mutually exclusive?
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5. Chapter 5 Exercise 34
P(A1) = .20, P(A2) = .40, and P(A3) = .40. P(B1|A1) = .25. P(B1|A2) = .05,
and P(B1|A3) = .10.
Use Bayes' theorem to determine P(A3|B1). (Round your answer to 4
decimal places.)
Want to download the Complete Weekly Assignment of QNT/561
Class..?? Click QNT 561 Weekly Learning Assessments
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6. Chapter 5 Exercise 40
Solve the following:
a. 20! 17!
b. 9P3
c. 7C2
Chapter 6 Exercise 4
Which of these variables are discrete and which are continuous random
variables?
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7. a. The number of new accounts established by a salesperson in a year.
b. The time between customer arrivals to a bank ATM.
c. The number of customers in Big Nick’s barber shop.
d. The amount of fuel in your car’s gas tank.
e. The number of minorities on a jury.
f. The outside temperature today.
Chapter 6 Exercise 14
The U.S. Postal Service reports 95% of first-class mail within the same
city is delivered within 2 days of the time of mailing. Six letters are
randomly sent to different locations.
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8. a. What is the probability that all six arrive within 2 days? (Round your
answer to 4 decimal places.)
b. What is the probability that exactly five arrive within 2 days? (Round
your answer to 4 decimal places.)
c. Find the mean number of letters that will arrive within 2 days. (Round
your answer to 1 decimal place.)
d-1. Compute the variance of the number that will arrive within 2 days.
(Round your answer to 3 decimal places.)
d-2. Compute the standard deviation of the number that will arrive within
2 days. (Round your answer to 4 decimal places.)
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9. Chapter 6 Exercise 20
In a binomial distribution, n = 12 and π = .60.
a. Find the probability for x = 5? (Round your answer to 3 decimal
places.)
b. Find the probability for x ≤ 5? (Round your answer to 3 decimal
places.)
c. Find the probability for x ≥ 6? (Round your answer to 3 decimal
places.)
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10. Chapter 6 Exercise 26
A population consists of 15 items, 10 of which are acceptable.
In a sample of four items, what is the probability that exactly three are
acceptable? Assume the samples are drawn without replacement.
(Round your answer to 4 decimal places.)
Chapter 7 Exercise 4
According to the Insurance Institute of America, a family of four spends
between $400 and $3,800 per year on all types of insurance. Suppose
the money spent is uniformly distributed between these amounts.
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11. a. What is the mean amount spent on insurance?
b. What is the standard deviation of the amount spent? (Round your
answer to 2 decimal places.)
c. If we select a family at random, what is the probability they spend
less than $2,000 per year on insurance per year? (Round your
answer to 4 decimal places.)
d. What is the probability a family spends more than $3,000 per
year? (Round your answer to 4 decimal places.)
Click here and download QNT 561 Week 3 Weekly Learning Assessments
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12. Chapter 7 Exercise 10
The mean of a normal probability distribution is 60; the standard
deviation is 5. (Round your answers to 2 decimal places.)
a. About what percent of the observations lie between 55 and 65?
b. About what percent of the observations lie between 50 and 70?
c. About what percent of the observations lie between 45 and 75?
Chapter 7 Exercise 14
A normal population has a mean of 12.2 and a standard deviation of 2.5.
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13. a. Compute the z value associated with 14.3. (Round your answer to 2
decimal places.)
b. What proportion of the population is between 12.2 and 14.3? (Round
your answer to 4 decimal places.)
c. What proportion of the population is less than 10.0? (Round your answer
to 4 decimal places.)
Chapter 7 Exercise 18
A normal population has a mean of 80.0 and a standard deviation of
14.0.
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14. a. Compute the probability of a value between 75.0 and 90.0. (Round
intermediate calculations to 2 decimal places. Round final answer to
4 decimal places.)
b. Compute the probability of a value of 75.0 or less. (Round
intermediate calculations to 2 decimal places. Round final answer to
4 decimal places.)
c. Compute the probability of a value between 55.0 and 70.0. (Round
intermediate calculations to 2 decimal places. Round final answer to
4 decimal places.)
Complete Learning Assessment Answers just a click away
QNT 561 Week 2 Weekly Learning Assessments
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15. Chapter 7 Exercise 28
For the most recent year available, the mean annual cost to attend a
private university in the United States was $26,889. Assume the
distribution of annual costs follows the normal probability distribution
and the standard deviation is $4,500.
Ninety-five percent of all students at private universities pay less than
what amount? (Round z value to 2 decimal places and your final answer
to the nearest whole number.)
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16. About Author
This article covers the topic for the University of Phoenix
QNT 561 Week 2 Weekly Learning Assessments. The author is working
in the field of education from last 5 years. This article covers the
weekly learning assessment of QNT 561 Week 2 from UOP. Other
topics in the class are as follows:
QNT 561 Week 3 Weekly Learning Assessments
QNT 561 Week 4 Weekly Learning Assessments
QNT 561 Week 5 Weekly Learning Assessments
QNT 561 Week 6 Weekly Learning Assessments
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