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Overview:In this unit students will:
• use real-life situations to show the purpose for using random sampling to make inferences about a population. • understand that random sampling guarantees that each element of the population has an equal opportunity to be selected in the sample. • compare the random sample to the population, asking questions like, “Are all the elements of the entire population represented in the sample?” and “Are the elements represented proportionally?” • make inferences given random samples from a population along with the statistical measures. • learn to draw inferences about one population from a random sampling of that population. • draw informal comparative inferences about two populations. • deal with small populations and determine measures of center and variability for a population. • compare measures of center and variability and make inferences. • use graphical representations of data to compare measures of center and variability. • begin to develop understanding of the benefits of the measures of center and variability by analyzing data with both methods. • understand that when they study large populations, random sampling is used as a basis for the population inference. • understand that measures of center and variability are used to make inferences on each of the general populations. • make comparisons for two populations based on inferences made from the measures of center and variability. Enduring Understandings: • 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. • 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. • Use measures of center and measures of variability for numerical data from random samples to draw informal comparative inferences about two populations. |
Vocabulary
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Unit 4: Lesson 1-3 Examples
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