Fundamental principles of inferential statistics are presented in lecture (3 hrs) augmented by computer labs using Excel (2 hrs). Essential topics include sampling methods; descriptive statistics; counting and probability; binary, normal, and other probability distributions; confidence intervals; hypothesis testing; inferences from two samples; correlation and regression. Optional topics include goodness-of-fit and contingency tables; ANOVA; nonparemetrics; and statistical process control.
Meets MnTC Goal 4
Course Effective Dates: 8/21/06 – Present
Outline of Major Content Areas
Bell curve
Confidence Intervals
Descriptive Statistics
Further Topics including;
Inferences from two samples, Correlation and regression
Goodness-of-fit and contingency tables,ANOVA,Nonparametric statistics,Statistical process control
Hypothesis Testing
Probability
Learning Outcomes
apply the Wilcoxon rand-sum-test for two independent samples
test claims about proportions
Critically analyze statistical claims
Explore data independently and draw justifiable conclusions
Present convincing statistical arguments backed up by persuasive graphics
State conclusions of hypothesis tests carefully and precisely
apply Poisson distribution to practical problems
apply binomial probability distribution to practical problems
apply rank correlation analysis
apply runs test for randomness
apply the Kruskal-Wallis test
apply the Wilcoxon signed-ranks test for matched pairs
apply the classical definition of probability
apply the normal distribution to practical problems
apply the sign test
calculate and interpret various measures of center (mean, media, mode, midrange)
calculate and interpret various measures of position (quartiles, percentiles, z-scores)
calculate and interpret various measures of variation (range, interquartile range, standard deviation)
compare variations in two samples
distinguish among the classical, experimental, and subjective methods of calculating probability
estimate a population mean using small samples: Student-
estimate a population mean using small samples: Student-T
estimate a population proportion
estimate a population standard deviation: chi square
explain the concept of correlation
explain the significance of the Central Limit Theorem
find linear and other regressions
make inferences about two means: independent samples
make inferences about two proportions
make inferences from matched pairs
perform one-way ANOVA analysis
perform two-way ANOVA analysis
represent data in various pictorial forms
summarize data with frequency tables
test claims about means
test claims about standard deviation or variance
use the addition rule in calculating probability
Minnesota Transfer Curriculum Goal Area(s) and Competencies Goal 04 — Mathematical/Logical Reasoning
Clearly express mathematical/logical ideas in writing.
Explain what constitutes a valid mathematical/logical argument(proof).