Learning Targets

There are twenty Learning Targets for this course, of which ten are designated as Core targets due to their nature in Statistics and the other ten are designated as Supplemental.

Data Collection (DC): I can design and assess data collection plans.

• DC.1 - I can identify if a variable is categorical or quantitative
• DC.2 - I can identify and state the population, parameter, and statistic for a scenario
• DC.3 - CORE I can identify aspects of a study’s design and assess potential strengths and weaknesses of these aspects
• DC.4 - CORE I can identify possible confounding variables and what can be done to correct for them
• DC.5 - Explain the importance of random sampling and random assignment in a data collection plan

Graphical Displays of Data (GD): I can create, explain, and assess graphical displays of data.

• GD.1 - CORE I can identify, produce using statistical software, and describe appropriate and effective graphical displays for a scenario
• GD.2 - I can determine approximate summary statistics that describe the distribution when provided with a graphical display of data

Numerical Summaries of Data (NS): I can create, explain, and assess numerical summaries of data.

• NS.1 - CORE I can identify, produce, and describe the appropriate numerical summaries for a scenario using a statistical software package
• NS.2 - CORE I can describe how numerical summaries change from sample to sample
• NS.3 - I can describe how sample size impacts the accuracy of a statistical analysis
• NS.4 - I can explain how the relationship between the numerical summaries can be used to describe the shape of a distribution (skewed left, skewed right, or symmetric) and how outliers impact various summary statistics
• NS.5 - CORE I can predict what the distribution of a variable would look like when provided with numerical summaries
• NS.6 - I can explain how variability plays a role in statistical analyses.

Statistical Inference (SI): I can determine and use the appropriate statistical inference technique to answer an authentic real-life application research question.

• SI.1 - CORE I can describe what role statistical inference plays in terms of the population and sample
• SI.2 - CORE I can identify the most appropriate statistical analyses for a given scenario
• SI.3 - I can explain what the confidence level means for a given scenario
• SI.4 - CORE I can estimate the value of an unknown population numerical summary from sample data
• SI.5 - CORE I can apply hypothesis testing procedures to infer about relationships and group differences in the population
• SI.6 - I can explain what a p-value means for a given scenario
• SI.7 - I can identify whether an error is a false positive or false negative for a given scenario