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
Statistics 311 J. McLean Sloughter Midterm Exam review list Ch. 1 Population vs. sample Representative sample Parameter vs. statistic Types of data Quantitative, qualitative, discrete, continuous, nominal, ordinal, interval, ratio Loaded questions Nonresponse Missing data Correlation vs. causation Observational study vs. experiment Cross-sectional, retrospective, prospective Confounding Blinding Double-blinding Randomization Random sample vs. simple random sample vs. probability sample Systematic sampling Convenience sampling Stratified sampling Cluster sampling Multistage sampling Ch. 2 Characteristics of data – center, variation, distribution, outliers, time Frequency distribution Histogram Relative frequency Cumulative frequency Bar graph / pareto chart Pie chart Scatterplot Time-series graph Ch. 3 Mean Median Mean vs. median in skewed data Range Standard deviation Empirical rule z-score quartiles percentiles boxplot Ch. 4 Event Simple event Sample space Probability Complement Addition rule Multiplication rule Disjoint Mutually exclusive Conditional probability Tree diagram With replacement vs. without replacement Bayes’ theorem Simulations Fundamental counting rule Factorial Permutations Combinations Ch. 5 Random variable Probability distribution Discrete vs. continuous random variable Mean/expected value & standard deviation for a probability distribution Identifying unusual events Binomial distribution requirements for a binomial binomial probability formula mean & standard deviation for a binomial Poisson distribution Requirements for a Poisson Poisson probability formula Mean & standard deviation for a Poisson Identifying Poisson vs. binomial Ch. 6 Normal distribution Uniform distribution Standard normal distribution Density curve Finding probabilities from z-scores Finding z-scores Changing z-scores into values Using a normal distribution to find percentiles Sampling distributions Central limit theorem Sampling distribution of sample means Normal approximation to the binomial Continuity correction [STOP HERE] Ch. 7 Point estimate Confidence interval Confidence level Margin of error Confidence intervals for proportions Sample size calculation for proportions Confidence intervals for means Known standard deviation versus unknown standard deviation Sample size calculation for means Student t distribution Degrees of freedom Confidence interval for standard deviation Chi-square distribution