Academic Standard

Data, Probability and Statistics
Tennessee Diploma Project
Grade range: 
9 to 12
Conceptual StrandThe Data Analysis and Probability Standard recommends that students formulate questions that can be answered using data and addresses what is involved in gathering and using the data wisely. The basic concepts and applications of probability are also addressed, with an emphasis on the way that probability and statistics are related.Guiding QuestionHow do students experiences with the collection and analysis of data enable them to reason statistically and understand the various purposes of surveys, observational studies, and experiments?
Elements within this Standard
Course Level Expectation
Describe, interpret, and apply quantitative data.
Evaluate and critique various ways of collecting data and using information based on data published in the media.
Use data and statistical thinking to draw inferences, make predictions, justify conclusions and identify and explain misleading uses of data.
Develop an understanding of probability concepts in order to make informed decisions.
Check For Understanding
Collect, represent and describe both linear and non-linear data developed from contextual situations.
Organize and display data using appropriate methods (including spreadsheets and technology tools) to detect patterns and departures from patterns.
Read and interpret data from a two-way table.
Understand the impact of various sampling methods and use them to draw valid conclusions.
Calculate measures of central tendency and spread (variance and standard deviation).
Use technology to find the appropriate regression equation for both linear and non-linear data.
Recognize when the correlation coefficient measures goodness of fit and does not imply causation.
Know the Empirical Rule for one, two and three standard deviations for a normal distribution.
Use data to detect patterns.
Design simple experiments to collect data to answer questions of interest.
Evaluate published data by considering the source, the design of the study and the analysis and representation (or misrepresentation) of the data.
Investigate bias and the phrasing of questions during data acquisition to formulate reasonable conclusions,
Apply both theoretical and experimental probability to analyze the likelihood of an event.
State Performance Indicator
Compute, compare and explain summary statistics for distributions of data including measures of center and spread.
Compare data sets using graphs and summary statistics.
Analyze patterns in a scatter-plot and describe relationships in both linear and non-linear data.
Apply the characteristics of the normal distribution.
Determine differences between randomized experiments and observational studies.
Find the regression curve that best fits both linear and non-linear data (using technology such as a graphing calculator) and use it to make predictions.
Determine/recognize when the correlation coefficient measures goodness of fit.
Apply probability concepts such as conditional probability and independent events to calculate simple probability.