Getting Ready for Data Management

Eight tutor-led lessons that turn Grade 11 Functions fluency into the counting, probability, and data-organizing skills Grade 12 Data Management opens with.

Who it's for: Students finishing Grade 11 Functions (MCR3U) and heading into Grade 12 Data Management (MDM4U), in a small tutor-led group of four. MCR3U never touches counting or statistics, so most of this is genuinely new: counting principle, permutations, combinations, probability rules, and organizing data.

✓ Applies the Fundamental Counting Principle and factorial notation, and chooses correctly between nPr and nCr instead of guessing which formula to use.✓ Calculates probability using the complement rule, the addition rule for overlapping events, and the multiplication rule for dependent and independent events.✓ Organizes raw data into frequency tables and grouped class-interval distributions, and computes mean, median, mode, and an estimated mean from grouped data.✓ Computes variance, standard deviation, and z-scores by hand, and uses the empirical rule to estimate what percent of a data set falls within a range.✓ Walks into the first week of Grade 12 Data Management already fluent in the vocabulary and formulas its Counting, Probability, and Data units assume on day one.

The 8-lesson plan

Slides are what your tutor works from in the live lesson. The practice module is homework: do it before the next lesson.

1

Numbers Behind the Data: Fractions, Percent, Exponents, and Factorial Notation

Rebuild fast fraction, ratio, percent, and exponent arithmetic and introduce factorial notation, the toolkit every counting and probability formula in MDM4U runs on.

2

The Fundamental Counting Principle: Counting Without Listing Everything

Use the Fundamental Counting Principle, multiplying choices at each stage, to count outcomes for multi-stage events with repetition and restrictions, tying to Lesson 1's factorials.

3

Permutations: Arranging Distinct Objects in Order

Count ordered arrangements of distinct objects using the permutation formula nPr, derived from Lesson 2's counting principle, distinguishing full arrangements from subsets.

4

Combinations: Choosing Without Order

Count selections where order does not matter using nCr, derived from nPr, and build the skill of reading a word problem to decide permutation versus combination.

5

Probability Basics: Sample Spaces, Complements, and the Addition Rule

Define probability as favorable outcomes over total outcomes using the counting tools from Lessons 2-4, then apply the complement and addition rules.

6

Conditional Probability and Independence

Compute conditional probability P(A given B), test events for independence, apply the multiplication rule, and use tables and tree diagrams for compound-event probability.

7

Organizing Data: Frequency Tables, Grouped Data, and Central Tendency

Organize raw data into frequency tables and grouped class-interval distributions, and compute mean, median, and mode from both raw and grouped data, opening MDM4U's Organizing Data unit.

8

Measures of Spread: Variance, Standard Deviation, and Reading Z-Scores

Compute range, variance, and standard deviation by hand for a data set, calculate and interpret z-scores, and take a first look at the normal distribution's empirical rule.

Reserve a seat (4 per cohort)