No, she only ordered one wheel for each triangle No, she only ordered one wheel for each triangle. She should have order 30 wheels. 3 = #of wheels.

Slides:



Advertisements
Similar presentations
Level 1 Multivariate Unit
Advertisements

5 Number Summary Box Plots. The five-number summary is the collection of The smallest value The first quartile (Q 1 or P 25 ) The median (M or Q 2 or.
Vocabulary for Box and Whisker Plots. Box and Whisker Plot: A diagram that summarizes data using the median, the upper and lowers quartiles, and the extreme.
Information for teachers This PowerPoint presentation gives some examples of analysis statements. Students own answers will differ based on their choice.
Vocabulary box-and-whisker plot quartiles variation
Chapter 21 Basic Statistics.
Describing Data Using Numerical Measures. Topics.
3-5: Exploratory Data Analysis  Exploratory Data Analysis (EDA) data can be organized using a stem and leaf (as opposed to a frequency distribution) 
6.8 Compare Statistics from Samples MM1D3a: Compare summary statistics (mean, median, quartiles, and interquartile range) from one sample data distribution.
A Short Tour of Probability & Statistics Presented by: Nick Bennett, Grass Roots Consulting & GUTS Josh Thorp, Stigmergic Consulting & GUTS Irene Lee,
 The mean is typically what is meant by the word “average.” The mean is perhaps the most common measure of central tendency.  The sample mean is written.
Measurement Variables Describing Distributions © 2014 Project Lead The Way, Inc. Computer Science and Software Engineering.
Summary Statistics and Mean Absolute Deviation MM1D3a. Compare summary statistics (mean, median, quartiles, and interquartile range) from one sample data.
The field of statistics deals with the collection,
NAME ____________________________________ DATE ____________________ PERIOD ______Samples & Populations: Problem 2.3 – Choosing Random Samples You are going.
PPDAC Cycle.
2-6 Box-and-Whisker Plots Indicator  D1 Read, create, and interpret box-and whisker plots Page
Claim 1 Smarter Balanced Sample Items Grade 7 - Target H Draw informal comparative inferences about two populations. Questions courtesy of the Smarter.
MM2D1: Using sample data, students will make informal inferences about population means and standard deviations b. Understand and calculate the means and.
Agenda Message: 1. Weekly Basics Quarter 2 # 5 Due Friday 12/4/ Unit 3 Folder Project Due Thursday 12/3/ Unit 4 SLM Due Thursday 12/3/15. 11/30/15.
6-3 Measures of Variation I CAN make a box-and-whisker plot. I CAN find the interquartile range of a set of numbers. I CAN find the mean absolute deviation.
7 th Grade Math Vocabulary Word, Definition, Model Emery Unit 4.
Box-and-Whisker Plots
Lesson – Teacher Notes Standard:
Recapping: Distribution of data.
M7Plus Unit-10: Statistics CMAPP Days (Compacted Days 1 – 5 )
Box-and-Whisker Plots
Box-and-Whisker Plots
Box-and-Whisker Plots
Measures of Central Tendency (center) Measure of Variability (spread)
You need: Pencil Agenda Scrap Paper AP log Math book Calculator
BOX-and-WHISKER PLOT (Box Plot)
Box-and-Whisker Plots
Range between the quartiles. Q3 – Q1
Inferences to the population
Math Review #3 Jeopardy Random Samples and Populations
Shape of Distributions
Box-And-Whisker Plots
Bellwork: Monday.
Box-and-Whisker Plots
Bell Ringer Create a Box Plot 7, 15, 2, 14, 8, 3, 15, 7
5 points piece Homework Check
Claim 1 Smarter Balanced Sample Items Grade 7 - Target H
2.Find the value of q 2.Find the value of x 38 7q + 44.
Lesson – Teacher Notes Standard:
(-4)*(-7)= Agenda Bell Ringer Bell Ringer
Tuesday.
Box-And-Whisker Plots
Box-And-Whisker Plots
Homework: Maintenance Sheet 28 via Study Island- Answer all 30 questions in diagnostic test
Box Plots CCSS 6.7.
MGSE7.SP.3/MGSE7.SP.4: I can use measure of center and measures of variability for numerical data from random samples to draw informal comparative inferences.
Maintenance Sheet Due Wednesday
Box-and-Whisker Plots
Box and Whisker Plots and the 5 number summary
Box-and-Whisker Plots
3rd Nine Weeks Benchmark *graded **NO CURVE
I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.
No, she only ordered one wheel for each triangle No, she only ordered one wheel for each triangle. She should have order 30 wheels. 3 = #of.
Box-and-Whisker Plots
Homework: Maintenance Sheet 28 via Study Island- Answer all 30 questions in diagnostic test
Maintenance Sheet Due Wednesday
Homework Due Friday- Maintenance Sheet 22
Homework Due Friday- Study Island-Maintenance Sheet 25
BOX-and-WHISKER PLOT (Box Plot)
Tuesday.
Tuesday.
Homework Due Friday- Study Island-Maintenance Sheet 25
Maintenance Sheet Due Wednesday
Presentation transcript:

No, she only ordered one wheel for each triangle No, she only ordered one wheel for each triangle. She should have order 30 wheels. 3 = #of wheels needed for each tricycle, x= number of tricycles and y = total number of wheels needed. 3(15) = 45

Twice her hourly rate is 24 per hour. She works 51 hours (11 over 40) Manager’s Rate Twice her hourly rate is 24 per hour. She works 51 hours (11 over 40) 11 x 24 = 264 40 x 12 = 480 264 + 480 = 744

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations. What is a 5 point summary?

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations. Box plot

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations. Box-whisker diagram

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations. 5

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.

MGSE7.SP.3 Informally assess the degree of visual overlap of two numerical data distributions with similar variabilities, measuring the difference between the medians by expressing it as a multiple of the interquartile range. MGSE7.SP.4: I can use measure of center and measures of variability for numerical  data  from random samples to draw informal comparative inferences about two populations.