Montana Math MT.CORE.DATA.INT.6.a
The Standard
- 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: Using technology strategically, represent two quantitative data distributions on scatter plots, Describing verbally how the variables are related, Using technology to find the least-squares regression line (line of best) fit for two quantitative variables, Understanding that the line of best fit minimizes the square of the residuals, and Understanding correlation as a measure of linear association and using technology, compute the correlation coefficient of a linear relationship.
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: Using technology strategically, represent two quantitative data distributions on scatter plots,
2026 Montana Mathematics Content Standards · Data Reasoning and Probability
Teacher's field guide
What This Standard Means
What Students Need to Do
- Students pair two measurements from the same day, such as daily high and low temperatures in Browning on the Blackfeet Reservation. They use a spreadsheet to plot the pairs and check whether the points follow a roughly straight line. They explain what the pattern means for those days.
What Mastery Looks Like
- A student plots each daily pair as one point and labels both axes with units. They describe the direction of the pattern, how closely points follow a line, and any unusual points. They can use the pattern to estimate a low without claiming the high causes it.
Common Misconceptions
- Students may put highs and lows on separate graphs instead of plotting paired values. They may match readings from different dates or think every point must sit on a line. Some mistake a pattern for proof that one temperature causes the other.
How to Assess It
- Exit ticket: Plot these sample Browning (high, low) temperature pairs in °F using a spreadsheet: (40,22), (45,25), (50,29), (55,33), (60,36). Label the axes and describe the pattern in one sentence.
Lesson moves
Ways to Teach It
Print dated high and low cards from public Browning weather records; students match dates and plot the pairs in Desmos.
Ask, “Do warmer daily highs in Browning tend to go with warmer daily lows, and which points complicate that claim?”
Show three scatter plots, one positive, one negative, and one scattered; students sort them and circle points far from a trend.
Use public Browning weather data from the Blackfeet Reservation to estimate tomorrow’s low from its forecast high, then check the recorded low.
Keep exploring
Related Standards
- MT.7.SP.3
Visually analyze two data distributions to compare measures of central tendency and variability.
- 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 contex...
- 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 represent...
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