MTH 209AW - Statistics - Extended Hours

1. Apply standard measures of descriptive statistics.
   1. Manipulate summation notation as it applies to mean, variance and standard deviation.
   2. Apply the midpoint formula to a weighted mean, mean from a frequency table/distribution as well as class marks for histograms.
   3. Follow the order of operations with emphasis on grouping symbols such as square roots and absolute value.
   4. Calculate, describe, and apply measures of center (mean, median, mode).
   5. Calculate, describe, and apply measures of variation (standard deviation, variance range).
   6.  Calculate, describe, and apply percentiles.
   7. Calculate, describe, and apply graphs (frequency distributions, histograms, stem and leaf plots, box and whisker plots).
2. Demonstrate understanding of statistical inference.
   1. Plot points and intervals on a number line as it applies to confidence intervals and z score comparison.
   2. Represent an inequality as an interval on a number line as it applies to confidence intervals and the comparison of probabilities.
   3. Compute the distance between two points on a number line as it applies to comparing test statistics with critical values as well as placing mean and standard deviation on a number line.
   4. Calculate powers of a number as it relates to the understanding of the binomial probability formula.
   5. Apply the complement, union and intersection as it relates to determining probability.
   6. Evaluate algebraic expressions and solve linear equations of one variable as it would relate to correlation, regression and minimum sample sizes.
   7. Identify different methods of data collection.
   8. Calculate and describe basic probability.
   9. Calculate probability using the binomial distribution, the normal distribution, and the central limit theorem.
   10. Use correlation and regression to describe relationships between numerical variables.
   11. Calculate confidence intervals to estimate population averages and proportions.
3. Demonstrate an understanding of the logic of statistical inference.
   1. Order decimal numbers as it applies to hypothesis testing conclusions – both p-value to level of significance and comparison of critical value to test statistic.
   2. Convert between fractions, decimals and percent as it applies to hypothesis testing for proportions and computing test statistics.
   3. Compute and apply signed number arithmetic for z score, t score, chi square, and other summary statistics.
   4. Manually perform all of the steps of a hypothesis test for a claim about the population mean.
   5. Demonstrate understanding of the significant level of a test and the use of p-values in statistical software.
   6. Determine the appropriate test statistic and make inferences for a variety of models, including single sample mean (large and small sample), proportion and variance, two sample mean and proportion, Chi Square and ANOVA.
   7. Determine the appropriate non-parametric test statistic and make inferences for a variety of models, including sign test, Wilcoxon Signed-Rank test for Matched Pairs, Kruskal-Wallis Test and Rank Correlation.
4. Communicate an understanding of statistical concepts in writing.
5. Demonstrate knowledge of a statistical computer software package.