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Theoretical vs. Experimental Probability PPT & Guided Notes BUNDLE

Rated 4.67 out of 5, based on 9 reviews
4.7 (9 ratings)
;
Mister Math
453 Followers
Grade Levels
6th - 9th
Subjects
Standards
CCSS7.SP.C.5
CCSS7.SP.C.6
CCSS7.SP.C.7
CCSS7.SP.C.7a
CCSS7.SP.C.7b
Formats Included
  • Zip
Pages
33 pages
$3.75
List Price:
$5.25
You Save:
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Easel Activities Included
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      This Probability MEGA BUNDLE is just what you've been looking for to assist students in learning about likelihood, simple probability, and experimental/theoretical probability! Included in this bundle, you will find:Outcomes & Events PowerPoint LessonOutcomes & Events Guided Notes (coincides
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    Description

    Standards

    5

    Reviews

    9

    Q&A

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    Description

    This BUNDLE includes a PowerPoint Lesson and a corresponding Guided Notes Packet to assist students in learning about theoretical and experimental probability. Students will learn the concepts of theoretical and experimental probability, as well as how to find the probabilities of each. Plenty of real-life examples are included to give students ample opportunities to practice the skills. Overall, the 21-slide PowerPoint and 6-page guided notes packet covers the following topics:

    • Theoretical Probability
    • Using Theoretical Probability
    • Experimental Probability
    • Making Predictions
    • Comparing Theoretical & Experimental Probability

    The presentation also comes fully animated, with animations triggered by mouse click (or presentation pointer)! An answer key is provided for the guided notes packet, as well.

    You'll SAVE MONEY when you purchase these resources with this BUNDLE!

    Want to learn more about what's included in this bundle? Click the links above to get more information about each included resource!

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    © Copyright 2021 Mister Math, ALL RIGHTS RESERVED. Permission is granted to copy pages specifically designed for student and/or teacher use by the original purchaser or licensee ONLY. You may not share the activities with anyone else unless additional licenses are purchased. Reproducing, copying, editing, distributing, selling, or placing any part of this product on the Internet is strictly prohibited. Doing so is a violation of the Digital Millennium Copyright Act (DMCA).

    Total Pages
    33 pages
    Answer Key
    Included
    Teaching Duration
    N/A
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    Standards

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    to see state-specific standards (only available in the US).
    CCSS7.SP.C.5
    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.
    CCSS7.SP.C.6
    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.
    CCSS7.SP.C.7
    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.
    CCSS7.SP.C.7a
    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.
    CCSS7.SP.C.7b
    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?

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