# MAT-183 Objectives

## MAT-183  Statistics I/Lab

### Unit 1

• Differentiate between descriptive and inferential statistics
• Identify types of data
• Identify the measurement level of a variable
• Identify basic sampling techniques
• Organize data using frequency distributions
• Represent frequency distributions graphically
• Represent data using bar graphs, time plots, and circle graphs
• Use statistical software to generate random samples
• Use statistical software to draw bar graphs, line graphs, circle graphs, and histograms

### Unit 2

• Summarize data using mean, median, and mode
• Describe data using range, variance, and standard deviation
• Identify the position of a data point by using percentiles and standard scores
• Produce stem and leaf displays and box and whisker plots
• Use statistical software to produce descriptive statistics

### Unit 3

• Determine the number of possible outcomes using a tree diagram
• Find the total number of possible outcomes using the multiplication rule
• Calculate the number of permutations of n things taken r at a time
• Calculate the number of combinations of n things taken r at a time
• Determine sample spaces
• Find the probability of an event using relative frequencies
• Find the probability of a compound event
• Find the conditional probability of an event

### Unit 4

• Construct a probability distribution for a discrete random variable
• Find the expected value and standard deviation for a discrete random variable
• Calculate binomial probabilities
• Find the mean and standard deviation for a binomial distribution
• Use statistical software to generate binomial probability distributions
• Use statistical software to solve problems using a binomial distribution

### Unit 5

• Identify the properties of a normal distribution
• Find the area under the standard normal distribution for various intervals
• Transform a normally distributed random variable into a standard normal variable
• Find specific data values for given areas under a normal distribution
• Use statistical software to solve problems using a normal distribution

### Unit 6

• State the Central Limit Theorem
• Use the Central Limit Theorem to solve problems involving the distribution of the sample mean for large samples
• Use the normal distribution to approximate probabilities for a binomial

### Unit 7

• Distinguish between point estimates and interval estimates
• Find the confidence interval for m using a large sample
• Find the confidence interval for m using a small sample
• Find the confidence interval for the binomial proportion p
• Determine the minimum sample size for estimating m to within a specified margin of error
• Determine the minimum sample size for estimating p to within a specified margin of error (with and without prior information)
• Use statistical software to produce confidence intervals for m

### Unit 8

• Structure a classical test of hypothesis
• Test means for one-sample (using large and small samples)
• Test for a proportion

### Unit 9

• Test the difference between means for dependent samples
• Test for the difference between means for two independent samples (large or small)
• Test for the difference between two proportions

### Unit 10

• Draw a scatter diagram
• Find the equation of the least squares regression line
• Use the least squares regression line to produce point estimates
• Compute the standard error of the estimate
• Find the confidence interval for the dependent variable
• Compute the linear correlation coefficient
• Test for a significant linear correlation
• Compute the coefficient of determination
• Use statistical software to determine the least squares regression line and linear correlation coefficient

### Unit 11

• Test two variables for independence using chi-square
• Test a distribution for goodness of fit using chi-square