Download Business Statistics - myANC - Arkansas Northeastern College

Business and Technical Division
Departmental Course Syllabus
BU 21013: Business Statistics
I.
Course Catalog Description
This is a statistical methods course covering the collection, analysis, and presentation of data for business
purposes. Also, includes the study of averages and dispersions, sampling, statistical inference, probability,
tests of hypotheses, estimation, regression and correlation.
II.
Course Rationale
Our efforts to understand our world by collecting and analyzing information of all kinds appears to be an
unending process. These efforts often are guided by the use of methods from the field of statistics. The
purpose of this course is for the students to learn the basic concepts of applied statistics so that the student
will be able to improve their ability to make better decisions and to improve their ability to measure and
cope with changing conditions in our professional and personal lives.
III.
Course Objectives
After successful completion of this course, the student will be able to:
 Describe the purpose of data collection and analysis
 Develop the ability to calculate and interpret various statistical measures
 Perform probability tests of various hypotheses, using results to draw inferences and make
estimations
 Utilize various statistical techniques to test and demonstrate trends and correlations
 Describe how statistical results are used for decision-making purposes in the business world.
IV.
Course Prerequisites
Grade “C” or better in MA 14043, College Algebra.
V.
Required Texts and Materials
 Basic Statistics for Business and Economics (with Formula Card), 7th Edition. Lind, Marchal, &
Wathen. 2011. McGraw-Hill/Irwin
 Study Guide for use with Statistical Techniques in Business & Economics; 14th Edition. Lind,
Marchal, & Wathen. Prepared by Kathleen Whitcomb. 2010. McGraw-Hill/Irwin.
 TI-30Xa Scientific Calculator (or equivalent hand-held calculator without Statistical Calculations)
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VI.
Grading Scale
Grading Scale (%)
90 - 100.0
A
80 – 89.9
B
70 – 79.9
C
60 – 69.9
D
0 – 59.9
F
VII.
Course Policies: Grades
Grades of "Incomplete":
The current College policy concerning incomplete grades will be followed in this course. Incomplete grades
are given only in situations where unexpected emergencies prevent a student from completing the course
and the remaining work can be completed the next semester. The instructor is the final authority on
whether a student qualifies for an incomplete. Incomplete work must be finished by mid-term of the
subsequent semester or the “I” will automatically be recorded as an “F” on the student’s transcript.
VIII.
Course Policies: Technology
Email: Arkansas Northeastern College has partnered with Google to host email addresses for ANC students.
myANCmail accounts are created for each student enrolled in the current semester and is the email address
the instructor will use to communicate with the student. The student accesses the email account by going to
http://mail.google.com/a/smail.anc.edu and using his/her first and last name, separated by a period for the
username. The default password is the Student ID, no hyphens. If the student cannot access the student
email, he/she should contact the MITS department at 762-1020 ext 1150 or ext 1207 or send an email to
[email protected].
Internet: This course has a web component on myANC.
Computer Labs: In addition to general-purpose classrooms, a number of computer laboratories are
provided for instructional and student use. These networked laboratories are state-of-the-art and fully
equipped with computers, printers, Internet connections and the latest software. The labs are open to
students enrolled in one or more credit hours at the College.
Technology Support: A lab assistant is generally present in the computer lab in B202 for assistance in using
the College computers. These assistants cannot help the student with course assignments; specific
questions regarding the technology requirements for each course should be directed to the instructor of the
course. Problems with myANC or College email accounts should be addressed by email to
[email protected].
IX.
Course Policies: Student Expectations
Disability Access: Arkansas Northeastern College is committed to providing reasonable accommodations
for all persons with disabilities. This syllabus is available in alternate formats upon request. Students with
disabilities who need accommodations in this course must contact the instructor at the beginning of the
semester to discuss needed accommodations. No accommodations will be provided until the student has
met with the instructor to request accommodations. Students who need accommodations must be
registered with Johnny Moore in Statehouse Hall, 762-3180.
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Academic Integrity Policy: Academic dishonesty in any form will not be tolerated. Students are expected to
do their own work. Plagiarism, using the words of others without express permission or proper citation, will
not be tolerated. Any cheating (giving or receiving) or other dishonest activity will, at a minimum, result in a
zero on that test or assignment and may be referred, at the discretion of the instructor, to the Department
Chair and/or Vice President of Instruction for further action. If you are uncertain as to what constitutes
academic dishonesty, please consult the Academic Integrity Policy for further details.
(http://www.anc.edu/docs/Academic_Integrity_Policy.pdf)
Learning Assistance Center: The Learning Assistance Center (LAC) is a free resource for ANC students. The
LAC provides drop-in assistance, computer tutorials and audio/visual aids to students who need help in
academic areas. Learning labs offer individualized instruction in the areas of mathematics, reading, writing,
vocabulary development and college study methods. Tutorial services are available on an individual basis for
those having difficulty with instructional materials. The LAC also maintains a shelf of free materials
addressing specific problems, such as procedures for writing essays and term papers, punctuation reviews,
and other useful materials. For more information, visit the LAC website at http://www.anc.edu/LAC or stop
by room L104 in the Adams/Vines Library Complex.
Other Student Support Services: Many departments are ready to assist students with reaching their
educational goals. Students should check with their advisors; the Learning Assistance Center, Room L104;
Student Support Services, Room S145; and Student Success, Room L101 to find the right type of support.
X.
Course Policies: First Day Handout
All students receive a First Day Handout following the format of the most current first day handout
template. The First Day Handout details the specifics of the instructor’s course policies and procedures.
XI.
Unit and Instructional Objectives:
Unit 1: Data, Statistics, and Probability Foundation Concepts
Rationale: Effectively utilizing statistical methods requires a foundation of data, statistical, and
probability concepts. An understanding of these concepts provides a vital basis for understanding
probability and statistical applications.
Objectives: The student will be able to:
1. Explain why we study statistics.
2. Explain what is meant by descriptive statistics and inferential statistics.
3. Distinguish between a qualitative variable and a quantitative variable.
4. Describe how a discrete variable is different from a continuous variable.
5. Distinguish among the nominal, ordinal, interval, and ratio levels of measurement.
6. Prepare a frequency table using qualitative data.
7. Present a frequency table as a bar chart or a pie chart.
8. Organize quantitative data into a frequency distribution.
9. Present a frequency distribution for quantitative data using histograms, frequency polygons, and
cumulative frequency polygons.
10. Calculate the arithmetic mean, weighted mean, median, mode, and mode.
11. Explain the characteristics, uses, advantages, and disadvantages of each measure of location.
12. Identify the position of the mean, median, and mode for both symmetric and skewed distributions.
13. Compute and interpret the range, mean deviation, variance, and standard deviation.
14. Describe the characteristics, uses, advantages, and disadvantages of each measure of dispersion.
15. Apply Chebyshev’s theorem and the Empirical Rule to a set of observations.
16. Develop and interpret a dot plot.
17. Compute and understand quartiles, deciles, and percentiles.
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18. Construct and interpret box plots.
19. Compute and understand the coefficient of skewness.
20. Draw and interpret a scatter diagram.
21. Construct and interpret a contingency table
22. Define probability.
23. Describe the classical, empirical, and subjective approaches to probability.
24. Explain the terms experiment, event, outcome, permutations, and combinations.
25. Define the terms conditional probability and joint probability.
26. Calculate probabilities using the rules of addition and rules of multiplication.
27. Use a tree diagram to organize and compute probabilities.
Unit 2: Probability, Sampling, and Application to Confidence Intervals and Hypothesis Testing
Rationale: Results of sampling and surveys enable us to make sound business and personal decisions
based on statistical analysis of data. Inferential statistical methods provide the necessary means for such
data analysis.
Objectives: The student will be able to:
1. Define the terms probability distribution and random variable.
2. Distinguish between discrete and continuous probability distributions.
3. Calculate the mean, variance, and standard deviation of a discrete probability distribution.
4. Describe the characteristics of and compute probabilities using the binomial probability distribution.
5. Describe the characteristics of and compute probabilities using the Poisson probability distribution.
6. Describe the difference between discrete and continuous distributions.
7. Compute the mean and the standard deviation for a uniform distribution.
8. Compute probabilities by using the uniform probability distribution.
9. List the characteristics of the normal probability distribution.
10. Define and calculate z values.
11. Determine the probability an observation is between two points on a normal probability distribution.
12. Determine the probability an observation is above (or below) a point on a normal probability distribution.
13. Explain when a sample is the only feasible way to learn about a population.
14. Describe methods to select a sample.
15. Define and construct a sampling distribution of the sample mean.
16. Explain the central limit theorem.
17. Use the central limit theorem to calculate probabilities of selecting possible sample means from a
specified population.
18. Define a point estimate.
19. Define level of confidence.
20. Construct a confidence interval for the population mean when the population standard deviation is
known.
21. Construct a confidence interval for the population mean when the population standard deviation is
unknown.
22. Construct a confidence interval for a population proportion.
23. Determine the sample size for an attribute or a variable.
24. Describe a hypothesis and hypothesis testing.
25. Describe the five-step hypothesis-testing procedure.
26. Distinguish between a one-tailed and a two-tailed test of hypothesis.
27. Conduct a test of a hypothesis about a population mean.
28. Conduct a test of a hypothesis about a population proportion.
29. Define Type I and Type II errors.
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Unit 3: Analysis of Multiple Samples and Prediction
Rationale: Sound business and medical applications require verification of study results, predictions with
a degree of confidence, and analysis of "treatment" effects. This unit provides the means and methods for
such analysis.
Objectives: The student will be able to:
1. Conduct a test of a hypothesis about the difference between two independent population means.
2. Conduct a test of a hypothesis about the difference between two population proportions.
3. Conduct a test of a hypothesis about the mean difference between dependent observations.
4. Describe the difference between dependent and independent samples.
5. Describe characteristics of the F distribution.
6. Conduct a test of a hypothesis to determine whether the variances of two populations are equal.
7. Discuss the general concept of analysis of variance.
8. Conduct a test of hypothesis among three or more treatment means.
9. Organize data into a one-way ANOVA table.
10. Develop confidence intervals for the difference in treatment means.
11. Describe characteristics of a dependent and independent variable.
12. Calculate and interpret the coefficient of correlation, the coefficient of determination, and the standard
error of estimate.
13. Conduct a test of hypothesis to determine whether the coefficient of correlation in the population is zero.
14. Calculate the least squares regression line.
15. Construct and interpret confidence and prediction intervals for the dependent variable.
16. Describe the relationship between several independent variables and a dependent variable using multiple
regression analysis.
17. Set up, interpret, and apply an ANOVA table
18. Compute and interpret the multiple standard error of estimate, the coefficient of multiple determination,
and the adjusted coefficient of multiple determination.
19. Conduct a test of hypothesis to determine whether regression coefficients differ from zero.
20. Conduct a test of hypothesis on each of the regression coefficients.
21. Use residual analysis to evaluate the assumptions of multiple regression analysis.
22. Evaluate the effects of correlated independent variables.
23. Describe and use qualitative independent variables.
24. Describe the characteristics of the chi-square distribution.
25. Conduct a test of hypothesis comparing an observed set of frequencies to an expected distribution.
26. Conduct a test of hypothesis to determine whether two classification criteria are related.
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