## BUS 224 - Statistical Analysis for Business

### Course Description

Effective: 2014-08-01

Discusses the business statistics topics typically covered in business degree programs. Covers frequency distributions, descriptive measures, probability concepts, probability distributions, sampling, hypotheses testing for means and proportions, Chi-square distribution, simple linear regression and briefly, multiple linear regression.
Credits - 4 Lecture - 4 hours Total 4 hours per week.
4 credits

### General Course Purpose

This course is formed from Business Statistics I (BUS 221) and II (BUS 222) to meet the business statistics requirements of a business degree program. It is designed, therefore, for a student who plans to transfer to a four-year college or university to receive a baccalaureate degree in business field. The student will acquire knowledge of certain basic terminology and methods in descriptive and inferential statistics.

### Course Prerequisites/Corequisites

Prerequisite: MTH 163

### Course Objectives

• Organizing and Displaying data
• organize ungrouped data into a frequency distribution
• construct different types of graphs using statistical software
• Descriptive Measures
• arrange ungrouped data into an array, and determine the mean, median, mode, percentiles and quartiles
• compute the range, variance, and standard deviation
• recognize the shape of the distribution?symmetrical and asymmetrical
• identify the modal class, median class, and class width of a given frequency distribution
• generate summary statistics using statistical software
• Discrete Probability Distributions
• compute expected value and variance of a discrete distribution
• state the required conditions for the use of the binomial distribution
• compute expected value and variance of a binomial distribution
• with the use of formula and table, solve problems involving binomial distribution
• recognize the conditions under which it is appropriate to use the Poisson distribution
• solve problems involving the Poisson distribution
• Continuous Probability Distribution
• describe the characteristics of normal distribution and standardized normal distribution
• solve normal curve problems using table
• normal approximation to the binomial distribution problems
• demonstrate the use of the normal distribution in business problem solving
• Sampling and Sampling Distributions
• distinguish between probability and non-probability sampling
• recognize random sampling techniques
• understand the sampling distribution of sample means
• Confidence Intervals for Single Population Mean and Proportion
• know the difference between point estimates and interval estimates
• calculate confidence intervals for mean and proportion
• compute appropriate sample size
• construct confidence interval using statistics package
• Hypothesis Testing for Single Population Mean and Proportion
• formulate null and alternative hypotheses
• understand the important of controlling ?
• determine the critical value using z-table, and t-table
• calculate the test statistic using appropriate distribution
• write conclusion in word
• Hypothesis Testing for Two Populations
• solve problems testing the difference in two means
• find p-value
• construct confidence intervals to estimate the difference in the means of two populations
• Simple Linear Regression and Correlation
• create and interpret scatter diagrams
• develop a regression model by the method of least squares
• check model assumptions using residual plots and normal probability plot
• measure the relationship among data through the calculation of the coefficients of determination and correlation
• Multiple Linear Regression
• Using Excel or Minitab
• Analysis of Categorical Data
• compare theoretical frequencies to actual frequencies using chi-square goodness-of-fit test
• determine whether the two variables are independent using chi-square test of independence

### Major Topics to be Included

• Organizing and displaying data
• Measures of central tendency and variability
• Basic probability concepts and problems
• Use of probability distributions: Binomial and Poisson, and use of the normal distribution
• Sampling and sampling distributions
• Confidence intervals for the population mean and proportion using normal distribution
• Basic hypothesis testing