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Data Analysis: Part 4. Lesson 7.3 & 7.4. Data Analysis: Part 4. MM2D1. Using sample data, students will make informal inferences about population means and standard deviations. a. Pose a question and collect sample data from at least two different populations.

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data analysis part 4

Data Analysis: Part 4

Lesson 7.3 & 7.4

data analysis part 41
Data Analysis: Part 4
  • MM2D1. Using sample data, students will make informal inferences about population means and standard deviations.
  • a. Pose a question and collect sample data from at least two different populations.
  • b. Understand and calculate the means and standard deviations of sets of data.
  • c. Use means and standard deviations to compare data sets.
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Data Analysis: Part 4
  • d. Compare the means and standard deviations of random samples with the corresponding population parameters, including those population parameters for normal distributions.
  • Observe that the different sample means vary from one sample to the next.
  • Observe that the distribution of the sample means has less variability than the population distribution.
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Data Analysis: Part 4

Activation: Warm Up pg. 317 & Motivator

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Data Analysis: Part 4

EQ: In order to design and implement a statistical experiment on given data, what decisions must be made?

Today you will begin to learn about data analysis as we learn about different sampling techniques!!

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Data Analysis: Part 4
  • Stratified Random Sample- a random sample where the population is divided into two or more groups according to some criteria (called strata) such as grade level or geographical location
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Data Analysis: Part 4
  • Clustered Sample- a random sample where the population is divided into clusters based on some criteria such as homerooms, family members, or geographical locations. A clustered sample is especially helpful when the size of the clusters is UNKNOWN.
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Data Analysis: Part 4

Example for Stratified Random Sample

Refer to Problem #1 pg. 317 & Male Height chart on pg. 311 in Student Text

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Data Analysis: Part 4
  • Bias-The process of including too many data points that share a similar trait, not representative of the data.
  • Fact- The are a number ofdecisions to be made when designing and implementing a statistical experiment such as: Defining a question, identifying a target population, choosing a sampling technique, etc.
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Data Analysis: Part 4

Complete Problem #1 in Student Text Book pg. 323

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Data Analysis: Part 4

Homework: Pg. 139-141 (1-2)

Pg. 144-146 (1-7)

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Data Analysis: Part 4

TOTD: 7, 11, 16, 32, 49, 65, 78, 94, 103

Find the Mean, Median, Mode, Range, Interquartile Range, Variance, and Standard Deviation

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Data Analysis: Part 4

Activation: Warm Up pg. 317 & Motivator

Instruction: Notes on Stratified Random & Cluster Samples

Work: Complete Problem #1 in Student Text Book pg. 323

Assessment: Unit 4 Test

TOTD: Write the formulas to find the mean, median, range, variance, and standard deviation of data analysis