Statistics & Probability: Interpreting Categorical and Quantitative Data674 questions35 skills
Statistics & Probability: Interpreting Categorical and Quantitative Data
674 questions35 skills
174 questions8 skills
Represent data with plots on the real number line (dot plots, histograms, and box plots).
50 questions3 skills
Use statistics appropriate to the shape of the data distribution to compare center (median, mean) and spread (interquartile range, standard deviation) of two or more different data sets.
52 questions3 skills
Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).
119 questions6 skills
Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages. Recognize that there are data sets for which such a procedure is not appropriate. Use calculators, spreadsheets, and tables to estimate areas under the normal curve.
151 questions8 skills
Summarize categorical data for two categories in two-way frequency tables. Interpret relative frequencies in the context of the data (including joint, marginal, and conditional relative frequencies). Recognize possible associations and trends in the data.
83 questions4 skills
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.
83 questions4 skills
Fit a function to the data; use functions fitted to data to solve problems in the context of the data. Use given functions or choose a function suggested by the context. Emphasize linear, quadratic, and exponential models.
32 questions2 skills
Informally assess the fit of a function by plotting and analyzing residuals.
30 questions1 skill
Fit a linear function for a scatter plot that suggests a linear association.
14 questions1 skill
Interpret the slope (rate of change) and the intercept (constant term) of a linear model in the context of the data.
20 questions1 skill
Compute (using technology) and interpret the correlation coefficient of a linear fit.