MATH 1114 - Introduction to Statistics

• Completion of MATH 0230  or MATH 0240  
• Placement and concurrent registration in MATH 0140  
• MATH 0250/MATH 1100/MATH 1114 Placement or equivalent
• Algebra College Level
• MATH 1201/1210 Placement or equivalent
• MATH 1400 Placement or equivalent
• A score of 3 on Advanced Placement test Calculus AB
• A score of 3 on Advanced Placement test Calculus BC
• Concurrent registration in MATH 0140  

1. Arithmetic skills with whole numbers, integers, fractions/ratios, and decimals
2. Computational skills with percentages and decimals
3. Algebraic skills with linear, quadratic, and rational expressions and equations
4. Manipulative facility with square roots
5. Facility with graphing straight lines from knowledge of the equation, slope/intercept, or point/intercept
6. College level reading

1. Distinguish between the two basic types of statistics - descriptive and inferential.
2. Distinguish between observational studies and experiments, and distinguish among random, simple random, and other types of sampling procedures.
3. Identify different sources of bias in sampling and devise different methods of random assignment for experiments; distinguish between a population and a sample.
4. Identify data as continuous or discrete.
5. Accurately interpret graphical displays of data.
6. Construct frequency tables, histograms, box plots and stem-and-leaf plots from raw data.
7. Describe distributions using appropriate statistical vocabulary.
8. Calculate and analyze the following statistics: mean, median, mode, range, variance, standard deviation, percentile, and z-scores from frequency table data.
9. Calculate probabilities using the addition and multiplication rules, the fundamental counting principle, and sample spaces.
10. Construct a probability distribution for a random variable; calculate the mean, variance, standard deviation, and expected value for a discrete random variable; calculate probabilities, means and standard deviations for a binomial random variable.
11. Calculate z-scores and probabilities for a normally distributed random variable; use the normal probability distribution to approximate a binomial probability.
12. Apply the Central Limit Theorem to describe the sampling distribution of x and calculate probabilities; describe the sampling distribution of a sample proportion and calculate probabilities.
13. Calculate confidence intervals (using both large and small samples) for means and proportions; calculate sample sizes for means and proportions.
14. Use the normal probability distribution and the student’s t-distribution to test hypotheses about a mean or a proportion and calculate the p-value for each test; interpret the results of the test.
15. Test hypotheses about two means from independent samples and perform paired t-tests on dependent samples; interpret the results of the tests.
16. Interpret scatter plots as describing form, direction and strength of relationships in bi-variate data, and compute and interpret the correlation coefficient for linear bi-variate data.
17. Compute the least squares regression line and use it to make predictions, and interpret the meaning of the slope and intercept of the regression line.
18. Perform chi-square tests of goodness of fit, independence, and homogeneity.
19. Perform analysis of variance.
20. Use statistical software or a statistical calculator to find descriptive statistics for a data set, display the data, find normal and binomial probabilities, produce scatterplots, and perform linear correlation and regression analysis.

1. Descriptive statistics
2. Probability
3. Normal and binomial distributions
4. Hypothesis testing
5. T-tests
6. Correlation
7. Linear regression
8. Chi-square test
9. Analysis of variance
10. Statistical software