Upon completion of the course, the student should be able to achieve the objectives as identified under each topic below:
A. Organizing and Displaying Data
- organize ungrouped data into a frequency distribution
- construct different types of graphs using statistical software
B. Descriptive Measures
- arrange ungrouped data into an array, and determine the mean, median, mode, percentiles and quartiles
- for a given data, compute the range, variance, and standard deviation
- recognize the shape of the distribution-symmetric and asymmetric
- identify the modal class, median class, and class width of a given frequency distribution
- generate summary statistics using statistical software
C. Basic Probability Concepts
- define experiment, sample space
- list elementary events
- construct Venn diagram and probability matrices for two sets probability problems
- solve problems involving use of addition rule
- define independent events and dependent events
- solve problems involving use of multiplication rule
- compute conditional probabilities
D. Discrete Probability Distributions
- compute expected X (mean) and variance of a discrete random variable
- state the required conditions for the use of the binomial probability distribution
- compute expected X (mean) 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
E. Continuous Probability Distribution
- describe the characteristics of normal distribution and standardized normal distribution
- solve problems finding areas under a normal curve using a z-table
- approximate normal to the binomial distribution
- demonstrate the use of the normal distribution in business problem solving
F. Sampling and Sampling Distributions
- distinguish between probability and non-probability sampling
- recognize what is meant by simple random, systematic, stratified, and cluster samples
- define sampling distribution of the mean, and state the central limit theorem and its significance
- write the formulas for and compute the standard error of the mean and the standard error of the proportion
G. 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
H. Hypothesis Testing for Single Population Mean and Proportion
- state null and alternative hypothesis
- calculate cut-off point using z-table, t-table
- interpret the tradeoff between type I and type II error
- calculate observed value using appropriate distribution (z-distribution, t-distribution)
- reach conclusion of the testing
- use statistical package to conduct hypothesis testing using p-value
Major Topics to be Included:
A. Bayes' Theorem: Revising prior estimates
B. Hypergeometric Distribution
C. Uniform distribution
- 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
- Statistical analysis (descriptive statistics) using statistical package