Academic Standard

Data, Probability and Statistics
Initiative:
Tennessee Diploma Project
Set:
Mathematics
Type:
Standard
Code:
5
Grade range:
6
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

Grade Level Expectation
Understand the meaning of probability and how it is expressed.
Interpret representations of data from surveys and polls, and describe sample bias and how data representations can be misleading.
Check For Understanding
Understand that the probability of an event is a number between zero and one that expresses the likelihood of its occurrence.
Identify the probability of an event as the ratio of the number of its actual occurrences to the total number of its possible occurrences.
Express probabilities in different ways.
Understand the difference between probability and odds.
Analyze a situation that involves probability of an independent event.
Estimate the probability of simple and compound events through experimentation or simulation.
Apply procedures to calculate the probability of complimentary events.
Connect data sets and their graphical representations (such as bar graphs, circle, graphs, and stem-and-leaf plots).
Determine the sample space for a given situation.
Distinguish between a random and nonrandom sample.
Select the appropriate measure of center to describe a data set.
Predict the characteristics of a population based on the analysis of sample data.
State Performance Indicator
Determine the theoretical probability of simple and compound events in familiar contexts.
Identify features of graphs that may be misleading.
Determine whether or not a sample is biased.