BUS 308 (New) Reading feeds the Imagination/Uophelpdotcom

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BUS 308 (New) Reading feeds the
Imagination/Uophelpdotcom

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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
• BUS 308 Week 2 Quiz

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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 Each
  production run has a 5 reject rate.
• A classical (or theoretical) probability example
  is This die has six sides, so I should see the
  number 2 come up 1/6th of the time.
• What are some examples of probability outcomes in
  your work or life? How would looking at them in
  terms of probabilities help us understand what is
  going on?
• How does the normal curve relate to
  activities/things you are associated with?

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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 analyzing data sets is to
  find some summary descriptive statistics for key
  variables. For salary, compa, age, Performance
  Rating, and Service find the mean and standard
  deviation for 3 groups overall sample, Females,
  and Males. You can use either the Data Analysis
  Descriptive Statistics tool or the Fx average
  and stdev functions. Note Place data to the
  right, if you use Descriptive statistics, place
  that to the right as well
• 3. What is the probability for a
• a. Randomly selected person being a male in grade
  E?
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BUS 308 Week 1 Quiz (New)

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• 1. Question In statistical notation, M is to µ
  as s is to s.
• 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?

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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 307 Week 2 Quiz (Ash)

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• BUS 307 Week 2 Quiz (Ash)

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BUS 307 Week 3 DQ 1 Forecasting Models (Ash)

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• BUS 307 Week 3 DQ 1 Forecasting Models
• Forecasting Models. From Chapter 9, answer
  Discussion Question 1 Which forecasting
  techniques do you think Ford should have used to
  forecast changes in the demand, supply, and price
  of palladium? Time series models? Causal models?
  Qualitative models? Justify your answer and
  respond to at least two of your classmates
  postings.
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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 cant 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. Based on our sample, how do you interpret
  the results and what do these results suggest
  about the population means for male and female
  salaries?
• 2. Based on our sample data set, perform a
  2-sample t-test to see if the population male and
  female average salaries could be equal to each
  other.

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BUS 308 Week 2 Quiz (New)

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• 1. 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 5. Question Each different
  t-distribution is defined by which of the
  following?
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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. Is the average
  performance rating the same for all grades?
  (Assume variances are equal across the grades for
  this ANOVA.)
• 2. While it appears that average salaries per
  grade differ, we need to test this assumption. Is
  the average salary the same for each of the grade
  levels? (Assume equal variances, and use the
  Analysis toolpak function ANOVA.) Use the input
  table to the right to list salaries under each
  grade level.
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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
• Lets 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. Interpret the results.
  How do they compare with the findings in the week
  2 one sample t-test outcomes (Question 1)?
• 2. Using our sample data, construct a 95
  confidence interval for the mean salary
  difference between the genders in the population.
  How does this compare to the findings in week 2,
  question 2?
• 3. We found last week that the degrees compa
  values within the population. Do not impact compa
  rates. This does not mean that degrees are
  distributed evenly across the grades and genders.
  Do males and females have the same distribution
  of degrees by grade?
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BUS 308 Week 4 Quiz (New)

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• 1. 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.
• Question 4. Question The null hypothesis for
  the test of independence states that no
  correlation exists between the variables.
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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?
• 5. Question In a problem where
  average temperature and number of daylight hours
  are used to predict energy consumption in homes,
  what does the standard error of multiple estimate
  gauge?
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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 employees 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
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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 StatPlusmac LE
  function Correlation).
• a. Reviewing the data levels from week 1, what
  variables can be used in a Pearsons 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?
• e. Does this information help us answer our equal
  pay for equal work question?
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BUS 308 (New) Reading feeds the
Imagination/Uophelpdotcom

• For more course tutorials visit
• www.uophelp.com