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BUS 308 HELPS __is a truly special teacher is very wise and sees tomorrow in every student’s eyes

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BUS 308 HELPS Massive Success @ bus308helps.com

BUS 308 HELPS Massive Success

BUS 308 Entire Course (New)

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BUS 308 Week 1 DQ 1 Language

BUS 308 Week 1 DQ 2 Probability

BUS 308 Week 1 Quiz

BUS 308 Week 1 Problem Set

BUS 308 Week 1 Quiz (New)

BUS 308 Week 2 DQ 1 Hypotheses

BUS 308 Week 2 DQ 2 Variation

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BUS 308 Week 1 DQ 1 Language

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Discussion 1-1/Language Numbers and measurements are the language of business. Organizations look at results in many ways: expenses, quality levels, efficiencies, time, costs, etc. What measures does your department keep track of? Are they descriptive or inferential data, and what is the difference between these? (Note: If you do not have a job where measures are available to you, ask someone you know for some examples, or conduct outside research on an interest of yours, or use personal measures.)

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BUS 308 Week 1 DQ 2 Probability

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Things vary in life – virtually nothing (except physical standards such as the speed of light) we interact with is constant over time. Much of this variation follows somewhat predictable patterns that can be examined using probability. An example of a subjective probability is: “Cops usually do not patrol this road, so I can get away with speeding.” An empirical probability example is:

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BUS 308 Week 1 Problem Set

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1. For assistance with these calculations, see the Recommended Resources for Week One. Measurement issues. Data, even numerically code variables, can be one of 4 levels – nominal, ordinal, interval, or ratio. It is important to identify which level a variable is, as this impacts the kind of analysis we can do with the data. For example, descriptive statistics such as means can only be done on interval or ratio level data. Please list, under each label, the variables in our data set that belong in each group.. 2. The first step in

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BUS 308 Week 1 Quiz (New)

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Question : In statistical notation, M is to μ as s is to σ. Question 2. Question : A parameter refers to a sample characteristic. Question 3. Question : Data on the city from which members of a board of directors come represent interval data. Question 4. Question : In a frequency distribution such as a bell-shaped curve, what does the vertical height of the curve indicate? Question 5. Question : The z transformation makes data normal. Question 6. Question : Data on the ages of customers are ratio scale data. Question

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BUS 308 Week 1 Quiz

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1. Question : Data on the city from which members of a board of directors come represent interval data.

2. Question : Inferential statistics infer the characteristics of samples.

3. Question : The mode is which of the following?

4. Question : The standard error of the mean can be calculated by dividing μ by the square root of the number of values in the distribution.

5. Question : If a certifying agency raises the requirements for real estate agents, what sort of decision error is the agency protecting against?

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BUS 308 Week 2 DQ 1 Hypotheses

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Discussion 2-1/Hypotheses What is a hypothesis test? Why do we need to use them to make decisions about relating sample results to the population; why can’t we just make our decisions by the sample value?

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BUS 308 Week 2 DQ 2 Variation

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Variation exists in virtually all parts of our lives. We often see variation in results in what we spend (utility costs each month, food costs, business supplies, etc.). Consider the measures and data you use (in either your personal or job activities). When are differences (between one time period and another, between different production lines, etc.) between average or actual results important? How can you or your department decide whether or not the observed differences over time are important? How could using a mean difference test help?

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BUS 308 Week 2 Problem Set

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Problem Set Week Two Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the Included in the Week Two tab of theEmployee Salary Data Set are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean. 1. Below are 2 one-sample t-test comparing male and female average salaries to the overall sample mean.

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BUS 308 Week 2 Quiz (New)

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Question : What is the relationship between the power of a statistical test and decision errors? Question 2. Question : The desired sample depends on all of these factors except? Question 3. Question : What question does the z test answer? Question 4. Question : The desired sample size depends only the size of the population to be tested. Question

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BUS 308 Week 2 Quiz

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1. Question : How is the sum of squares unlike either the standard deviation or the variance?

2. Question : If sums of squares statistics are calculated for shoppers at three different retail outlets, what statistic will indicate the variability among those at each outlet?

3. Question : Which is the symbol used for the test statistic in ANOVA?

4. Question : If ANOVA reveals that four different departments have significantly different levels of productivity, what will a post-hoc test indicate?

5. Question : The independent t-test is based on which distribution?

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BUS 308 Week 3 DQ 1 ANOVA

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In many ways, comparing multiple sample means is simply an extension of what we covered last week. Just as we had 3 versions of the t-test (1 sample, 2 sample (with and without equal variance), and paired; we have several versions of ANOVA – single factor, factorial (called 2-factor with replication in Excel), and within- subjects (2-factor without replication in Excel). What examples (professional, personal, social) can you provide on when we might use each type? What would be the appropriate hypotheses statements for each example?

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BUS 308 Week 3 DQ 2 Effect Size

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Several statistical tests have a way to measure effect size. What is this, and when might you want to use it in looking at results from these tests on job related data?

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BUS 308 Week 3 Problem Set

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ASSIGNMENT WEEK 3 Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the (Note: Questions 1- 4 have additional elements to respond to below the analysis results.) 1. Last week, we found that the average performance ratings do not differ between males and females in the population. Now we need to see if they differ among the grades.

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BUS 308 Week 4 DQ 1 Confidence Intervals

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Discussion 4-1/Confidence Intervals Many people do not “like” or “trust” single point estimates for things they need measured. Looking back at the data examples you have provided in the previous discussion questions on this issue, how might adding confidence intervals help managers accept the results better? Why? Ask a manger in your organization if they would prefer a single point estimate or a range for important measures, and why? Please share what they say.

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BUS 308 Week 4 DQ 2 Chi-Square Tests

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Discussion 4-2/Chi-Square Tests Chi-square tests are great to show if distributions differ or if two variables interact in producing outcomes. What are some examples of variables that you might want to check using the chi-square tests? What would these results tell you?

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BUS 308 Week 4 Problem Set

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ASSIGNMENT WEEK 4 Let’s look at some other factors that might influence pay. Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use the 1. Using our sample data, construct a 95% confidence interval for the population's mean salary for each gender.

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BUS 308 Week 4 Quiz (New)

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Question : The goodness of fit test null hypothesis states that the sample data does not match an expected distribution. Question 2. Question : Statistical significance in the Chi-square test means the population distribution (expected) is not the source of the sample (observed) data. Question 3. Question : While rejecting the null hypothesis for the goodness of fit test means distributions differ, rejecting the null for the test of independence means the variables interact.

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BUS 308 Week 4 Quiz

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1. Question : With reference to problem 1, what statistic determines the correlation of experience with productivity, controlling for age in experience?

2. Question : In a problem where interest rates and growth of the economy are used to predict consumer spending, which of the following will increase prediction error?

3. Question : With reference to problem 3, how is the regression constant or the a value interpreted?

4. Question : Which of the following is a problem in simple regression?

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BUS 308 Week 5 DQ 1 Correlation

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Discussion 5-1/Correlation What results in your departments seem to be correlated or related to other activities? How could you verify this? Create a null and alternate hypothesis for one of these issues. What are the managerial implications of a correlation between these variables?

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BUS 308 Week 5 DQ 2 Regression

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Discussion 5-2/Regression At times we can generate a regression equation to explain outcomes. For example, an employee’s salary can often be explained by their pay grade, appraisal rating, education level, etc. What variables might explain or predict an outcome in your department or life? If you generated a regression equation, how would you interpret it and the residuals from it?

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BUS 308 Week 5 Final Paper (2 Papers)

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This tutorial contains 2 Different Papers The final paper provides you with an opportunity to integrate and reflect on what you have learned during the class. The question to address is: “What have you learned about statistics?” In developing your responses, consider – at a minimum – and discuss the application of each of the course elements in analyzing and making decisions about data (counts and/or measurements). The course elements include: · Descriptive statistics · Inferential statistics ·

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BUS 308 Week 5 Problem Set

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ASSIGNMENT WEEK 5 1. Create a correlation table for the variables in our (Use analysis ToolPak or StatPlus:mac LE function Correlation). a. Reviewing the data levels from week 1, what variables can be used in a Pearson’s Correlation Table (which is what Excel produces)? b. Place the table here. c. Using r= approximately .28 as the significant r value (at p = .05) for a correlation between 50 values, what variables are significantly related to salary? To compa? d. Looking at the above correlations – both significant or not – are there any surprises – by that I mean any relationships you expected to be meaningful and are not, and vice-versa?

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