CCSS_MATHAPhigh school
AP Statistics
Learn to collect, analyze, and draw conclusions from data -- aligned to the College Board AP Statistics curriculum. From exploring distributions and designing experiments to building confidence intervals and running hypothesis tests, this course gives you the reasoning skills to earn a 4 or 5 on exam day.
5units
17topics
232questions
~6hours
Course Units
Learning objectives
- Represent distributions of categorical data with bar charts and two-way tables
- Represent distributions of quantitative data with dotplots, histograms, stemplots, and boxplots
- Calculate and interpret measures of center (mean, median) and spread (range, IQR, standard deviation)
- Identify outliers using the 1.5 x IQR rule and describe their effect on summary statistics
- Use the normal distribution (z-scores, empirical rule, normal probability calculations) to model quantitative data
Learning objectives
- Describe the direction, form, and strength of a bivariate relationship from a scatterplot
- Calculate and interpret the correlation coefficient r and the coefficient of determination r-squared
- Construct and interpret a least-squares regression line, including slope and y-intercept in context
- Analyze residual plots to assess whether a linear model is appropriate
- Identify influential points and outliers in regression and describe their effect on the model
Learning objectives
- Distinguish between observational studies and experiments and explain why only experiments support causal conclusions
- Identify sources of bias (voluntary response, convenience sampling, response bias, undercoverage) in sampling designs
- Describe the principles of well-designed experiments: random assignment, replication, control, and blinding
- Explain the difference between random sampling and random assignment and what each allows you to conclude
- Evaluate the scope of inference (generalizability and causation) based on how a study was designed
Learning objectives
- Apply the addition rule (including for mutually exclusive events) and the multiplication rule (including for independent events)
- Calculate and interpret expected value and standard deviation of discrete random variables
- Determine probabilities using the binomial distribution and check its conditions (fixed n, independent trials, constant p)
- Determine probabilities using the geometric distribution for 'first success' problems
- Describe sampling distributions of sample proportions and sample means, including the Central Limit Theorem
Learning objectives
- Construct and interpret confidence intervals for a single proportion and a difference of two proportions
- Construct and interpret confidence intervals for a single mean (t-interval) and a difference of two means
- Conduct significance tests (z-test) for a single proportion and a difference of two proportions
- Conduct significance tests (t-test) for a single mean and a difference of two means
- Perform chi-square tests for goodness of fit, homogeneity, and independence
- Conduct inference for the slope of a least-squares regression line (t-test and confidence interval)
- Interpret p-values, confidence levels, Type I/Type II errors, and power in context
- Verify conditions (randomness, normality, independence/10% rule) before applying any inference procedure