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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.

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Presentation on theme: "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."— Presentation transcript:

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 of decisions 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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