Difference between revisions of "Stat 202 Objectives"
From Sean_Carver
(→Chapter 5) |
(→Chapter 5) |
||
| Line 36: | Line 36: | ||
== Chapter 5 == | == Chapter 5 == | ||
| − | * Given the mean and standard deviation for the raw | + | * Find mean and standard deviation, and other summary statistics, for a quantitative variable. |
| − | * Given the mean and standard deviation for the raw | + | * Given the mean and standard deviation for the raw data, compute the z-score for particular data points. |
| + | * Given the mean and standard deviation for the raw data, compute the raw score for particular z-scores. | ||
* Interpret a z-score as the number of standard deviations of a data point above the mean. | * Interpret a z-score as the number of standard deviations of a data point above the mean. | ||
* Know that, after transforming data to z-scores, the mean of the z-scores is 0. | * Know that, after transforming data to z-scores, the mean of the z-scores is 0. | ||
* Know that, after transforming data to z-scores, the standard deviation of the z-scores is 1. | * Know that, after transforming data to z-scores, the standard deviation of the z-scores is 1. | ||
| + | * Given several Normal probability plots, identify which looks most Normal (it should will be obvious). | ||
| + | * Use the Normal calculator in StatCrunch to compute percentiles and related quantities. | ||
| + | * Know the parameters for the standard Normal model (mean 0, standard deviation 1). | ||
| + | * Know that if the data follow a Normal distribution, the z-scores follow a standard Normal distribution. | ||
| + | * Know that if the data do NOT follow a Normal distribution, the z-scores do NOT follow Normal distribution either, although mean of the z-scores is 0 and the standard deviation is 1. | ||
Revision as of 18:19, 3 February 2018
By the end of the course, students will be able to ...
Chapter 1
- Given a data table and the story behind the data, identify the cases and list the variables.
- Identify a variable as either nominal, ordinal, identifier, binary, or quantitative.
Chapter 2
- Define and report the distribution of a categorical variable.
- Be able to convert between frequency, relative frequency, and percent.
- Tell when two plots of categorical data show the same distribution.
Chapter 3
- Define distribution of a quantitative variable.
- Create stem and leaf displays from data.
- Tell from a histogram whether a distribution is symmetric or left or right skewed.
- Tell whether a histogram is uniform, unimodal, bimodal, or multimodal and why.
- Tell whether a histogram shows outliers, or gaps.
- Describe how to compute the median.
- Describe how to compute the mean.
- Describe how to compute the lower and upper quartiles and the interquartile range (IQR).
- Describe how to compute the standard deviation.
- For summary statistics, describe the difference between resistant to outliers and sensitive to outliers.
- Compute the 5-number summary of data.
- Given data, compute the value for a specific percentile.
- Given data, compute the percentile for a specific value.
Chapter 4
- Identify the symmetry or left or right skew in boxplots.
- Comparing boxplots across groups, tell which groups have the greatest, and least, medians.
- Comparing boxplots across groups, tell which groups have the greatest, and least, interquartile range.
Chapter 5
- Find mean and standard deviation, and other summary statistics, for a quantitative variable.
- Given the mean and standard deviation for the raw data, compute the z-score for particular data points.
- Given the mean and standard deviation for the raw data, compute the raw score for particular z-scores.
- Interpret a z-score as the number of standard deviations of a data point above the mean.
- Know that, after transforming data to z-scores, the mean of the z-scores is 0.
- Know that, after transforming data to z-scores, the standard deviation of the z-scores is 1.
- Given several Normal probability plots, identify which looks most Normal (it should will be obvious).
- Use the Normal calculator in StatCrunch to compute percentiles and related quantities.
- Know the parameters for the standard Normal model (mean 0, standard deviation 1).
- Know that if the data follow a Normal distribution, the z-scores follow a standard Normal distribution.
- Know that if the data do NOT follow a Normal distribution, the z-scores do NOT follow Normal distribution either, although mean of the z-scores is 0 and the standard deviation is 1.
