## MGMT 290 - Quantitative Methods for Business

The course addresses a wide range of issues and questions using statistical techniques such as collection, analysis and interpretation of data, measures of central tendency and dispersion, probability and probability distributions, sampling and sampling distributions, estimation, statistical hypotheses testing, test of goodness of fit, regression and correlation. Problem solving for business and economics, social and physical sciences, engineering, etc. are used.

Credits: 3

Hours: 60 (Lecture Hours: 45; Laboratory Hours: 15)

Total Weeks: 15

Prerequisites:

One of Principles of Mathematics 11, Pre-Calculus 11, Foundations of Mathematics 11, CCP Math 040 or equivalent.

Non-Course Prerequisites:

None

Co-Requisites:

None

Course Content:
- Introduction to Statistics
- Describing, Exploring and Comparing Data
- Probability
- Probability Distributions
- Normal Probability Distributions
- Estimates and Sample Sizes
- Hypothesis Testing
- Inferences from Two Samples
- Correlation and Regression
- Analysis of Variance

- Non parametric Statistics

Learning Outcomes:
Upon successful completion of this course, the student should be able to:
- Define the terms statistics, population, sample, parameter, statistic, descriptive statistics, and statistical inference.
- Outline the basic steps in the statistical problem-solving methodology.
- Identify methods of obtaining samples.
- Discuss the types of tables and charts used to analyze and present numerical facts.
- Construct and interpret a frequency polygon, frequency distribution, and histogram.
- Compute central tendency measures such as arithmetic mean, median, and mode by formulas and with the aid of a
financial calculator.
- Compute measures of dispersion such as the range, standard deviation, and mean absolute deviation.
- Define probability and explain how sample probabilities are assigned.
- Differentiate between discrete and continuous random variables.
- Find expected value of a discrete random variable.
- Explain the concepts of conditional, independent and mutually exclusive events.
- Identify and compute binomial and Poisson Distributions
- Determine and utilize the properties of a normal distribution including calculating the probabilities and using z scores.
- State the steps required to
Produce a sampling distribution of sample means;
Compute the mean; and
Calculate the standard deviation of this sampling distribution.
- Compute estimates of population means, percentages, and variances using different levels of confidence.
- Determine the appropriate sample size used to estimate the population mean at different levels of confidence.
- Outline the steps of the hypothesis-testing procedure.
- Conduct one and two-sample hypothesis tests of means, and percentages for testing situations.
- Use the Anova testing procedure and F-distribution to arrive at statistical decisions.
- Perform Chi-sequare and contingency table tests.
- Calculate, use and interpret regression and correlation analysis.

- Identify and use nonparametric statistical methods.