Gizmos for Montana - Mathematics: Core Data Reasoning and Probability (2026 Content Standards adopted 2025)

This correlation lists the recommended Gizmos for this state's curriculum standards. Click any Gizmo title below for more information.

MT.CORE.DATA.LIT: Quantitative Literacy

MT.CORE.DATA.LIT.2: Ask a statistical question to determine whether there appears to be an association between two variables, design and carry out an investigation, and write a persuasive argument based on the results of the investigation.

MT.CORE.DATA.LIT.3: Distinguish between association and causation.

MT.CORE.DATA.INT: Visualizing, Summarizing, and Interpreting Data

MT.CORE.DATA.INT.1: Use technology to organize data, including very large data sets, into a useful and manageable structure.

MT.CORE.DATA.INT.2: Represent the distribution of univariate quantitative data with plots on the real number line, choosing a format most appropriate to the data set, and representing the distribution of bivariate quantitative data with a scatter plot.

MT.CORE.DATA.INT.3: Understand that standard deviation measures the variability of a data distribution, and calculate standard deviation using technology.

MT.CORE.DATA.INT.4: Interpret differences in the shape, center, and spread of quantitative data distributions, in context, accounting for possible effects of outliers on measures of central tendency and variability.

MT.CORE.DATA.INT.5: Compare and contrast two or more quantitative data distributions, using shape, center, and spread in context. This standard should incorporate cultural context relating to Montana Indigenous Peoples and local communities.

MT.CORE.DATA.INT.6: Analyze the relationship between two quantitative data distributions in context that have a linear association. This standard should incorporate cultural context relating to Montana Indigenous Peoples and local communities by:

MT.CORE.DATA.INT.6.a: Using technology strategically, represent two quantitative data distributions on scatter plots,

MT.CORE.DATA.INT.6.b: Describing verbally how the variables are related,

MT.CORE.DATA.INT.6.c: Using technology to find the least-squares regression line (line of best) fit for two quantitative variables,

MT.CORE.DATA.INT.6.d: Understanding that the line of best fit minimizes the square of the residuals, and

MT.CORE.DATA.INT.6.e: Understanding correlation as a measure of linear association and using technology, compute the correlation coefficient of a linear relationship.

MT.CORE.DATA.PROB: Probability

MT.CORE.DATA.PROB.1: Understand the concept of a sample space and describe events as subsets of a sample space.

MT.CORE.DATA.PROB.2: Understand the concepts of conditional probability and independence in context. This standard should incorporate cultural context relating to Montana Indigenous Peoples and local communities by:

MT.CORE.DATA.PROB.2.a: Determining whether two events, A and B, are independent by using two-way tables, tree diagrams, and/or Venn diagrams, and interpreting the answer in context.

Correlation last revised: 7/28/2026

Montana - Mathematics: Core Data Reasoning and Probability

2026 Content Standards | Adopted: 2025

MT.CORE.DATA.LIT: Quantitative Literacy

MT.CORE.DATA.INT: Visualizing, Summarizing, and Interpreting Data

MT.CORE.DATA.PROB: Probability