I started using Stick-n-Solve Foldables in my Math Interactive Notebooks last year and it worked great! There are a few things about these Stick-n-Solves that I really have enjoyed. First, my students no longer spend time copying down problems when we take notes. I always thought this was a waste of time. Now, the problems are on the foldable ready to be solved. The students like to cut and fold and glue while working in their notebooks. It gives them something tactile to do during class. Finally, the foldables are a built in review tool for your students. At the end of a unit, they can go back through their notebooks and solve all the problems on the Stick-n-Solves. Since the work is on the inside, they just open them up to check their answers. Each foldable in this set has two per page. My students are set up in partners, so I give one sheet to each partner pair to cut in half. There is no extra paper on these foldable templates (which means no little scraps of paper to trim off and end up all over the floor).
This Bundle focuses on Statistics and Probability and includes 9 Stick-n-Solve Foldables:
1. Probability – 7.SP.C.5
2. Simple Events – 7.SP.C.5, C.6
3. Probability Models – 7.SP.C.7, C.7.a, C.7.b
4. Compound Events – 7.SP.C.8, C.8.a, C.8.b
5. Tree Diagrams – 7.SP.C.8, C.8.a, C.8.b
6. Simulation – 7.SP.C.8, C.8.a, C.8.c
7. Statistics – 7.SP.A.1, A.2
8. Comparing Measures of Center – 7.SP.B, B.3, B.4
9. Comparing Measures of Variability – 7.SP.B, B.3, B.4
For each foldable, you will see two pictures. You will see a draft picture of notes for the topic, and a picture of the solutions on the inside of the foldable. For almost every topic covered, I’ve made a foldable. In total I have created about 50 Stick-n-Solve Foldables for 7th grade common core math and organized them into the following bundles:
1. Proportional Reasoning
2. Rational Numbers
4. Probability & Statistics
6. Scale & Construction
7. Vocabulary Diagrams
These activities can be found in my Math Interactive Notebook 7th Grade FOLDABLE BUNDLES at 15% or 25% off!!!
**Leave Feedback after your purchase to earn TpT credits!!**
Understand that statistics can be used to gain information about a population by examining a sample of the population; generalizations about a population from a sample are valid only if the sample is representative of that population. Understand that random sampling tends to produce representative samples and support valid inferences.
Use data from a random sample to draw inferences about a population with an unknown characteristic of interest. Generate multiple samples (or simulated samples) of the same size to gauge the variation in estimates or predictions. For example, estimate the mean word length in a book by randomly sampling words from the book; predict the winner of a school election based on randomly sampled survey data. Gauge how far off the estimate or prediction might be.
Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the centers by expressing it as a multiple of a measure of variability. For example, the mean height of players on the basketball team is 10 cm greater than the mean height of players on the soccer team, about twice the variability (mean absolute deviation) on either team; on a dot plot, the separation between the two distributions of heights is noticeable.
Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations. For example, decide whether the words in a chapter of a seventh-grade science book are generally longer than the words in a chapter of a fourth-grade science book.
Understand that the probability of a chance event is a number between 0 and 1 that expresses the likelihood of the event occurring. Larger numbers indicate greater likelihood. A probability near 0 indicates an unlikely event, a probability around 1/2 indicates an event that is neither unlikely nor likely, and a probability near 1 indicates a likely event.
Approximate the probability of a chance event by collecting data on the chance process that produces it and observing its long-run relative frequency, and predict the approximate relative frequency given the probability. For example, when rolling a number cube 600 times, predict that a 3 or 6 would be rolled roughly 200 times, but probably not exactly 200 times.
Develop a probability model and use it to find probabilities of events. Compare probabilities from a model to observed frequencies; if the agreement is not good, explain possible sources of the discrepancy.
Develop a uniform probability model by assigning equal probability to all outcomes, and use the model to determine probabilities of events. For example, if a student is selected at random from a class, find the probability that Jane will be selected and the probability that a girl will be selected.
Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process. For example, find the approximate probability that a spinning penny will land heads up or that a tossed paper cup will land open-end down. Do the outcomes for the spinning penny appear to be equally likely based on the observed frequencies?
Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation.
Math Interactive Notebook - Stick-N-Solve FOLDABLES Probability & Stats - 7th Gr
by Kimberly Wasylyk
is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License