- Course type: Self-paced
- Available Lessons: 16
- Average Lesson Length: 8 min
- New lessons are still being added
Watch a preview:chapter 1 / lesson 1Difference between Populations & Samples in Statistics
Course SummaryEnsure your seventh graders meet Common Core standards for statistics and probability with this math standards course. You can use the text and video lessons to create interesting class and homework assignments that are sure to capture your students' attention.
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2 chapters in Common Core Math Grade 7 - Statistics & Probability: Standards
Course Practice TestCheck your knowledge of this course with a 50-question practice test.
- Comprehensive test covering all topics
- Detailed video explanations for wrong answers
About the Course
Designed by educators, parents, scholars and state educational departments, the Common Core State Standards define a set of concepts and skills for seventh grade students to master. These standards aim to provide consistency in education across geographic locations. This collection addresses Common Core standards for statistics and probability, using engaging video and text lessons to teach the following topics:
- Difference between samples and populations
- Random sampling
- Using sample data to estimate parameters
- Measuring and calculating central tendency in data sets
- Spread in data sets
- Sample and population variance
- Comparing center and variability measurements for two sets of data
- Tables for frequency and relative frequency
- Interpreting and creating dot plots
- Probability formulas
- Probabilities for dependent and independent events
- Making predictions with experimental probability
- Compound event probability
- Finding expected values in games of chance
- Simulating frequencies of compound events
These lessons use clear, direct instruction and visual aids to help students understand populations and probability modeling. Each lesson is between five and ten minutes long, and can be displayed on any device that connects to the Internet. Use the practice questions to supplement assignments or test student proficiency.
Population Samples & Random Sampling (CCSS.MATH.CONTENT.7.SP.A.1)
Standard: 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.
The lessons that correspond to this standard teach students about the differences between populations and samples and the conditions and measures used in random sampling.
Drawing Inferences From Random Samples & Gauging Variations (CCSS.MATH.CONTENT.7.SP.A.2)
Standard: 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.
Students can use the lessons on this standard to explore how to estimate a parameter from sample data and learn about population and sample variance.
Measures of Variability in Data Sets (CCSS.MATH.CONTENT.7.SP.B.3)
Standard: 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.
The lesson for this standard teaches students how to compare center and variability measurements for two different sets of data.
Measures of Center and Variability (CCSS.MATH.CONTENT.7.SP.B.4)
Standard: 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.
These lessons show students how to understand and use measures of central tendency and sample variance.
Numerical Representations of Probability (CCSS.MATH.CONTENT.7.SP.C.5)
Standard: 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.
Use this lesson to teach students about probability formulas and examples of probabilities.
Probability Predictions (CCSS.MATH.CONTENT.7.SP.C.6)
Standard: 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.
The lesson on this standard show students how to use experimental probability to make predictions.
Probabilities of events(CCSS.MATH.CONTENT.7.SP.C.7)
Standard: 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.
Students can review these lessons to learn how to use probability formulas and find the probabilities of dependent and independent events.
Uniform Probability Models (CCSS.MATH.CONTENT.7.SP.C.7.A)
Standard: 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.
These lessons explain independent and dependent events and teach students how to create probability models.
Probabilities of Compound Events (CCSS.MATH.CONTENT.7.SP.C.8)
Standard: Find probabilities of compound events using organized lists, tables, tree diagrams, and simulation.
Use these lessons to help students with determining the probability of compound events and finding expected values in games of chance.
Fractional Nature of Compound Probabilities (CCSS.MATH.CONTENT.7.SP.C.8.A)
Standard: Understand that, just as with simple events, the probability of a compound event is the fraction of outcomes in the sample space for which the compound event occurs.
The lesson for this standard can teach students how to understand the probability of compound events as a combination of the probability of each single event.
Sample Spaces for Compound Events (CCSS.MATH.CONTENT.7.SP.C.8.B)
Standard: Represent sample spaces for compound events using methods such as organized lists, tables and tree diagrams. For an event described in everyday language (e.g., 'rolling double sixes'), identify the outcomes in the sample space which compose the event.
With these lessons, students learn how to work with the probabilities of compound events and identify likely outcomes in games of chance.
Simulating Compound Events (CCSS.MATH.CONTENT.7.SP.C.8.C)
Standard: Design and use a simulation to generate frequencies for compound events. For example, use random digits as a simulation tool to approximate the answer to the question: If 40% of donors have type A blood, what is the probability that it will take at least 4 donors to find one with type A blood?
Use these lessons to help students determine probabilities of compound events and simulate frequencies for compound events. Students also learn how to create their own simulations.
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