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Entire Courses of University of Phoenix

Get help for Entire Courses of University of Phoenix. We provide assignment, homework, discussions and case studies help for all subjects of University of Phoenix for Session 2017-2018.
 

AET 508 Adult Education and Training


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BCOM 231 Business Communication


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BIS 221 Introduction to Computer Applications and Systems


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BIO 101 Principles of Biology


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BIS 320 Business Information System


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BSA 310 Business Systems


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BSA 375 Fundamentals of Business systems Development


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BSA 510 IT Governance and Management


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FIN 420 Personal Financial Planning



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FIN 571 Corporate Finance



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FP 120 Essentials of Personal Finance


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GEN 480 Interdisciplinary Capstone Course

                      

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GEO 215 Geography


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HCA 230 Communication Skills for Health Care Professionals



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HCA 250 the Psychology Of Health

                      

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RES 351 Business Research



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RES 320 Foundations of Research



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REL 134 World Religious Traditions II


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QRB 501 Quantitative Reasoning for Business


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QNT 351 Quantitative Analysis for Business


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QNT 351 WEEK 1 Introduction to Statistical Thinking



Introduction to Statistical Thinking Worksheet
Complete the Introduction to Statistical Thinking Worksheet.
 Format your assignment consistent with APA guidelines.
 Click the Assignment Files tab to submit your assignment.

University of Phoenix Material


INTRODUCTION TO STATISTICAL THINKING

Directions: Complete the following questions. The most important part of statistics is the thought process, so make sure that you explain your answers, but be careful with statistics. The following statistics/probability problems may intrigue you and you may be surprised. The answers are not always as you might think.  Please answer them as well as you can by using common logic.

There are 23 people at a party. Explain what the probability is that any two of them share the same birthday.


A cold and flu study is looking at how two different medications work on sore throats and fever. Results are as follows:

Sore throat - Medication A: Success rate - 90% (101 out of 112 trials were successful)
Sore throat - Medication B: Success rate - 83%  (252 out of 305 trials were successful)

Fever - Medication A: Success rate - 71%  (205 out of 288 trials were successful)
Fever - Medication B:  Success rate - 68%  (65 out of 95 trials were successful)

Analyze the data and explain which one would be the better medication for both a sore throat and a fever.




QNT 351 WEEK 2 Descriptive Statistics – Real Estate Data Part 1


Descriptive Statistics – Real Estate Data Part 1

 Create an Excel® spreadsheet with the real estate data from the Individual Homework.

Prepare a frequency distribution for listing prices, including relative frequencies.

Create your frequency distribution as identified in Chapters 2, 3, and 4.



Create either a pie chart or a bar graph of the number of bedrooms in your 100 homes.

Evaluate your visual aid.............................................................................

Calculate measures of central tendency for both listing prices and square footages. Those measures are mean, median, and mode. ..........................................

Also calculate the standard deviation and variance for housing prices.  What do you conclude about the housing prices based on your data? 

What is the range of housing prices?  Does the range explain anything? .

Conclude whether Chebyshev's or Empirical Rule is more accurate with each of listing prices and square footages.

Format your assignment consistent with APA guidelines.

Click the Assignment Files tab to submit your assignment.




QNT 351 WEEK 3 Sampling Distributions – Real Estate Part 2



Sampling Distributions – Real Estate Part 2

Use the real estate data that you used for your learning team project that was due in Week 2.

Complete the Sampling Distributions - Real Estate Part 2 worksheet.

Format your assignment consistent with APA guidelines.

Click the Assignment Files tab to submit your assignment.

University of Phoenix Material

Sampling Distributions – Real Estate Part 2

Directions: Use the real estate data you used for your Week 2 learning team assignment. Analyze the data and explain your answers.

Review the data and for the purpose of this project please consider the 100 listing prices as a population.

Explain what your computed population mean and population standard deviation

Divide the 100 listing prices into 10 samples of n=10 each. Each of your 10 samples will tend to be random if the first sample includes houses 1 through 10 on your spreadsheet, the second sample consists of houses 11 through 20, and so on.

Compute the mean of each of the 10 samples and list them:

Compute the mean of those 10 means.

Explain how the mean of the means is equal, or not, to the population mean of the 100 listing prices from above.

Compute the standard deviation of those 10 means and compare the standard deviation of the 10 means to the population standard deviation of all 100 listing prices.

Explain why it is significantly higher, or lower, than the population standard deviation.

Explain how much more or less the standard deviation of sample means was than the population standard deviation. According to the formula for standard deviation of sample means, it should be far less. (That formula is σ = σ/√n  =  σ/√10  = σ/3.16  )  Does your computed σ  agree with the formula?

According to the Empirical Rule, what percentage of your sample means should be within 1 standard deviation of the population mean? Using your computed σ, do your sample means seem to conform to the rule?

According to the Empirical Rule, what percentage of your sample means should be within 2 standard deviations of the population mean? Again, do your sample means seem to conform to the rule?

You used the Empirical Rule because it really gives us more information (and because I asked you to), but truthfully you should have used Chebyshev’s Theorem. Even though Chebyshev’s doesn’t tell us much, why should you have used that one instead?


The United States employed a statistician to examine damaged planes returning from bombing missions over Germany in World War II. He found that the number of returned planes that had damage to the fuselage was far greater than those that had damage to the engines.  His recommendation was to enhance the reinforcement of the engines rather than the fuselages.  If damage to the fuselage was far more common, explain why he made this recommendation.




QNT 351 Week 4 Problems



A nylon rope maker claims its repelling rope's average breaking strength is at least 800 pounds.  A researcher sets up a hypothesis test regarding the breaking strength of the rope where Ho: μ ≤ 800.  where α = .05. 
Rewrite his null and alternative hypotheses as complete sentences. What does the hypothesis suggest about where the benefit of the doubt is being placed?  Explain your answer. 

What does it mean to make a type I error, and, specifically, what would constitute a type one error in this case?
In this case, is it appropriate to use  α = .05?  Explain why or why not.

what would we conclude if the sample average was much larger than 800 pounds?

what would we conclude if the sample average was slightly less than 800 pounds?

what if the sample average is much less than 800?

2, Pennsylvania Governor Tom Ridge has a  longstanding reputation for being "tough on crime."  His opponent is currently running ads that dispute this.  Before Ridge took office, the average criminal spent 12.5 years in prison before parole.  Ridge's opponent says that a random sample of forty-nine recent parolees spent an average of only eleven years in prison (the standard deviation in the sample was fourteen years).  Assuming you work for an independent newspaper, evaluate the claim made by the Ridge opponent.  What would you report to your readers? Test at the 05 percent level of significance.

Using the last problem calculate the 95 percent confidence interval.  Interpret this interval.




QNT 351 Week 5 Real Estate Regression Exercise



Real Estate Regression Exercise

Complete the Real Estate Regression Exercise.  This will be completed in class with your Learning Teams.  Each Learning Team will be required to present their results to the class. 
University of Phoenix Material

 Real Estate Regression Exercise

 Directions: Use the real estate data you used for your Week 2 learning team assignment. Analyze the data and explain your answers.
 You are consulting for a large real estate firm.  You have been asked to construct a model that can predict listing prices based on square footages for homes in the city you’ve been researching.  You have data on square footages and listing prices for 100 homes.

Which variable is the independent variable (x) and which is the dependent variable (y)?

Click on any cell. Click on Insert→Scatter→Scatter with markers (upper left).

To add a trendline, click Tools→Layout→Trendline→Linear Trendline

Does the scatterplot indicate observable correlation?  If so, does it seem to be strong or weak?

In what direction?


Click on Data→Data Analysis→Regression→OK. Highlight your data (including your two headings) and input the correct columns into Input Y Range and Input X Range, respectively.  Make sure to check the box entitled “Labels”.

What is the Coefficient of Correlation between square footage and listing price?

Does your Coefficient of Correlation seem consistent with your answer to #2 above? Why or why not?

What proportion of the variation in listing price is determined by variation in the square footage? What proportion of the variation in listing price is due to other factors?

Check the coefficients in your summary output. What is the regression equation relating square footage to listing price?

Test the significance of the slope. What is your t-value for the slope? Do you conclude that there is no significant relationship between the two variables or do you conclude that there is a significant relationship between the variables?

Using the regression equation that you designated in #3(d) above, what is the predicted sales price for a house of 2100 square feet?




QNT 275 Statistics for Decision Making


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QNT 275 WEEK 1 QUIZ



​Cross-section data are collected:

​on different elements for the same variable for different periods of time


​on different elements at the same point in time


​for a qualitative variable


​on the same variable for the same variable at different points in time

​A simple random sample is a sample drawn in such a way that:




QNT 275 WEEK 1 Statistics in Business


Statistics in Business

Purpose of Assignment

The purpose of this assignment is to have students demonstrate mastery of the foundational concepts that set the stage for the remainder of the course. Students apply those concepts to business research questions or problem situations to focus their thinking on statistical literacy for use in business decision-making.




QNT 275 WEEK 2 QUIZ



​We obtain the percentage of a category by:

​multiplying the frequency of that category by 100


​dividing the frequency of that category by 100

​multiplying the relative frequency of that category by 100




QNT 275 WEEK 3 QUIZ



​Which of the following is not a characteristic of the normal distribution?

​The curve is symmetric about the mean




QNT 275 WEEK 5 Business Problem


Business Problem

Hypothetical Business Problem

Hypothetical Business Problem: You are hired as a consultant for a large auto dealership organization. Your job is to look at their customer satisfaction surveys over the past 5 years and based on your analysis of that data, present recommendations to the senior management. Assume the data indicates a declining trend on the customer satisfaction rates.




QNT 275 Week 4 Practice Set Latest 2017 Version



1. Find z for each of the following confidence levels. Round to two decimal places.

90%   
95%   
96%
97%   
98%   
99%




QNT 275 Week 5 Practice Set


2. Find the value of x2 for 12 degrees of freedom and an area of .025 in the right tail of the chi square distribution curve. What is the value of chi-square? Round to three decimal places




QNT 275 Week 1 Practice Set



2. Indicate which of the following variables are quantitative and which are qualitative.

Note:
Spell quantitative and qualitative in lower case letters.

    The amount of time a student spent studying for an exam
    The amount of rain last year in 30 cities
    The arrival status of an airline flight (early, on time, late, canceled) at an airport
    A person's blood type
    The amount of gasoline put into a car at a gas station




OPS 571 Operations Management


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OI 370 Innovation For The 21st Century



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OI 361 Innovation, Design, & Creativity for A Competitive Advantage


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IT 240 Intro to LAN Technologies


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IT 205 Management of Information Systems


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IT 200 Digital Skills for the 21st Century


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ISCOM 352 Logistics Management


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IM 305 Data Modelling


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IM 300 Data Organization Architecture


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