Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
FINAL EXAM Review Sheet MATH 2600 You may (but are not required to) bring: 1. a graphing calculator (TI-83+ or equivalent), 2. two 8.5 inch by 11 inch sheets of paper of notes (infomally called "cheat sheets") 3. any of the following tables: the binomial table (Table II of Appendix A), the standard normal table (front cover of your text), the t-distribution table (front cover of your text), You should be able to: From a data set ( of size 30) Produce a stem-leaf plot Find the mean, standard deviation, and median Find the five number summary (min, Q1, median, Q3, max) Draw a box plot (box and whiskers plot) from this summary Describe a distribution (shape, center, spread, "quarters" of data set) From a frequency table Find the mean and standard deviation Sketch a histogram Apply Chebyshev's Rule <for any distribution> Empirical Rule <only appropriate for bell-shaped (mound-shaped)> Determine if an event is "common" or "uncommon" use 2-standard deviations from mean as a measure For probability Determine the sample space of an experiment, Determine the complement of an event Find theoretical probabilities under "equally likely" assumption Determine if events are independent (A and B are independent iff P(A and B) = P(A)P(B) or P(A|B)= P(A) or P(B|A) = P(B)) Addition rule P(A or B) = P(A) + P(B) – P(A and B), Multiplication rule P(A and B) = P(A|B)P(B) Counting using addition rule, multiplication rule, combinations, permutations, partitions Discrete probability distributions determining if a discrete probability distribution is valid (two conditions to check) mean (expected value) variancestandard deviation Bernoulli trials, Binomial experiments, Binomial distribution: n, p, q, X, x, P(X = x), Find probabilities of events of binomial experiments P(X = x) = binompdf(n,p,x) P(0 X x) = binomcdf(n,p,x) Continuous probability distributions uniform distribution normal distribution , N() ---- standard normal z ~ N() invnorm(Area,) and normcdf(Low, High, ) calculator functions interpretation (test #3, #5ce) _ Central Limit Theorem -- Sampling Distributions for the sample mean x Confidence intervals for the mean of a population Using ZInterval or TInterval as appropriate, Interpretations **Hypothesis Tests for claims about the population mean (one-tailed, two-tailed) --- Chapter 8 Using ZTest or TTest as appropriate, test statistic, p-value, null hypothesis, alternate hypothesis