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Data Analysis: Part 4

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

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  1. Data Analysis: Part 4 Lesson 7.3 & 7.4

  2. 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.

  3. 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.

  4. Data Analysis: Part 4 Activation: Warm Up pg. 317 & Motivator

  5. 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!!

  6. 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

  7. 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.

  8. Data Analysis: Part 4 Example for Stratified Random Sample Refer to Problem #1 pg. 317 & Male Height chart on pg. 311 in Student Text

  9. 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.

  10. Data Analysis: Part 4 Complete Problem #1 in Student Text Book pg. 323

  11. Data Analysis: Part 4 Homework: Pg. 139-141 (1-2) Pg. 144-146 (1-7)

  12. 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

  13. 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

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