Lesson Plan Day 1 Lesson Plan Day 2 Lesson Plan Day 3

Slides:



Advertisements
Similar presentations
DESCRIBING DISTRIBUTION NUMERICALLY
Advertisements

Descriptive Measures MARE 250 Dr. Jason Turner.
CHAPTER 4 Displaying and Summarizing Quantitative Data Slice up the entire span of values in piles called bins (or classes) Then count the number of values.
By the end of this lesson you will be able to explain/calculate the following: 1. Histogram 2. Frequency Polygons.
It’s an outliar!.  Similar to a bar graph but uses data that is measured.
ISE 261 PROBABILISTIC SYSTEMS. Chapter One Descriptive Statistics.
Statistics: Use Graphs to Show Data Box Plots.
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
An Introduction to Statistics. Two Branches of Statistical Methods Descriptive statistics Techniques for describing data in abbreviated, symbolic fashion.
1)Construct a box and whisker plot for the data below that represents the goals in a soccer game. (USE APPROPRIATE SCALE) 7, 0, 2, 5, 4, 9, 5, 0 2)Calculate.
Categorical vs. Quantitative…
To be given to you next time: Short Project, What do students drive? AP Problems.
© 2012 W.H. Freeman and Company Lecture 2 – Aug 29.
Statistics Unit Test Review Chapters 11 & /11-2 Mean(average): the sum of the data divided by the number of pieces of data Median: the value appearing.
(Unit 6) Formulas and Definitions:. Association. A connection between data values.
Interpreting Categorical and Quantitative Data. Center, Shape, Spread, and unusual occurrences When describing graphs of data, we use central tendencies.
AP Statistics. Chapter 1 Think – Where are you going, and why? Show – Calculate and display. Tell – What have you learned? Without this step, you’re never.
UNIT ONE REVIEW Exploring Data.
Chapter 1: Exploring Data
ISE 261 PROBABILISTIC SYSTEMS
Chapter 5 : Describing Distributions Numerically I
Statistics Unit Test Review
CHAPTER 2: Describing Distributions with Numbers
6th Grade Math Lab MS Jorgensen 1A, 3A, 3B.
NUMERICAL DESCRIPTIVE MEASURES
Laugh, and the world laughs with you. Weep and you weep alone
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Descriptive Statistics
DAY 3 Sections 1.2 and 1.3.
Please take out Sec HW It is worth 20 points (2 pts
Lesson 1: Summarizing and Interpreting Data
Displaying and Summarizing Quantitative Data
POPULATION VS. SAMPLE Population: a collection of ALL outcomes, responses, measurements or counts that are of interest. Sample: a subset of a population.
CHAPTER 1 Exploring Data
Unit 1: Inference and Conclusions from Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Describing Distributions
Elementary Statistics: Looking at the Big Picture
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Describing Distributions Numerically
Histograms and Measures of Center vs. Spread
Honors Statistics Review Chapters 4 - 5
Chapter 1: Exploring Data
CHAPTER 1 Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
CHAPTER 1 Exploring Data
Chapter 1: Exploring Data
CHAPTER 1 Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
CHAPTER 1 Exploring Data
Advanced Algebra Unit 1 Vocabulary
CHAPTER 1 Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
CHAPTER 1 Exploring Data
Chapter 1: Exploring Data
Chapter 1: Exploring Data
Presentation transcript:

Lesson Plan Day 1 Lesson Plan Day 2 Lesson Plan Day 3 Go over the 3 types of graphs Show video on histograms Do line plot with student ages Cover box and whisker plot Lesson Plan Day 2 Go over PPT Go over finding standard deviation Lesson Plan Day 3 Go over PPT (68-95-99.7 Rule)

Distributions And Their Shapes Statistics Distributions And Their Shapes

Introduction As stated before, statistics is all about data. Without data to talk about or to analyze or to question, statistics would not exist. Data sets are often summarized by graphs; the graphs are the first indicator of variability in the data, and provide a great visual for us to analyze.

Type of Graphs- Dot Plots Dot plots: A plot of each data value on a scale or number line.

Type of Graphs- Histograms Histograms: A graph of data that groups the data based on intervals and represents the data in each interval by a bar.

Type of Graphs- Box Plots Box plots: A graph that provides a picture of the data ordered and divided into four intervals that each contains approximately 25% of the data.

Day 2

Shape of Graphs Symmetry. When it is graphed, a symmetric distribution can be divided at the center so that each half is a mirror image of the other. Bell-shaped Roughly or somewhat symmetric

Shape of Graphs Number of peaks. Distributions can have few or many peaks. Distributions with one clear peak are called unimodal, and distributions with two clear peaks are called bimodal. When a symmetric distribution has a single peak at the center, it is referred to as bell-shaped.

Shape of Graphs Skewness. When they are displayed graphically, some distributions have many more observations on one side of the graph than the other. Distributions with fewer observations on the right are said to be positively skewed or skewed right; Distributions with fewer observations on the left are said to be negatively skewed or skewed left.

Shape of Graphs Uniform. When the observations in a set of data are equally spread across the range of the distribution, the distribution is called a uniform distribution. A uniform distribution has no clear peaks.

Shape of Graphs Outliers. Sometimes, distributions are characterized by extreme values that differ greatly from the other observations. These extreme values are called outliers. All of the above observations fall between 0 and 4, except for the one 9. As a "rule of thumb", a value is often considered to be an outlier if it is at least 1.5 interquartile ranges below the firstquartile (Q1), or at least 1.5 interquartile ranges above the third quartile (Q3).

Inference and Conclusions from Data Other than visually inspecting the graphs of data, we can analyze and compare the Center and the Spread of the data. Measures of center are mean, median, and mode, and for spread we use IQR, range, and standard deviation. Measures of Center Mean ( ): add all the values and divide by the number of data values – BALANCING POINT Median: middle value of an ordered set of data – SPLITS DATA IN HALF Mode- Most (Peaks)

Inference and Conclusions from Data Other than visually inspecting the graphs of data, we can analyze and compare the Center and the Spread of the data. Measures of center are mean, median, and mode, and for spread we use IQR, range, and standard deviation. Measures of Spread IQR (Inner Quartile Range): Q3-Q1 Range: Max - Min Standard Deviation: square root of the variance; measure of how spread out the data are from the mean.

Variance and Standard Deviation

Day 3

Relationship between mean and standard deviation

(68-95-99.7 Rule)

Visual of IQR vs Normal Distribution

Shape – look at a histogram, dotplot, or boxplot of the data When looking at the distribution of a set of data, you want to focus on the center and 2 other key characteristics: Shape Spread Shape – look at a histogram, dotplot, or boxplot of the data Symmetric Skewed Left Skewed Right

http://stattrek.com/statistics/charts/data-patterns.aspx?tutorial=ap