Math 140 Introductory Statistics. First midterm September

Similar documents
Chapter 3. Numerical Descriptive Measures. Copyright 2016 Pearson Education, Ltd. Chapter 3, Slide 1

Measures of Center. Mean. 1. Mean 2. Median 3. Mode 4. Midrange (rarely used) Measure of Center. Notation. Mean

Both the quizzes and exams are closed book. However, For quizzes: Formulas will be provided with quiz papers if there is any need.

Section3-2: Measures of Center

The Standard Deviation as a Ruler and the Normal Model. Copyright 2009 Pearson Education, Inc.

Chapter 6. y y. Standardizing with z-scores. Standardizing with z-scores (cont.)

Math 2311 Bekki George Office Hours: MW 11am to 12:45pm in 639 PGH Online Thursdays 4-5:30pm And by appointment

STAT 113 Variability

Normal Model (Part 1)

Measures of Variation. Section 2-5. Dotplots of Waiting Times. Waiting Times of Bank Customers at Different Banks in minutes. Bank of Providence

Math146 - Chapter 3 Handouts. The Greek Alphabet. Source: Page 1 of 39

Numerical Descriptions of Data

Data that can be any numerical value are called continuous. These are usually things that are measured, such as height, length, time, speed, etc.

2 Exploring Univariate Data

Lecture 2 Describing Data

Unit 2 Statistics of One Variable

appstats5.notebook September 07, 2016 Chapter 5

Describing Data: One Quantitative Variable

Some estimates of the height of the podium

3.1 Measures of Central Tendency

Simple Descriptive Statistics

Ti 83/84. Descriptive Statistics for a List of Numbers

STATISTICAL DISTRIBUTIONS AND THE CALCULATOR

1) What is the range of the data shown in the box and whisker plot? 2) True or False: 75% of the data falls between 6 and 12.

1 Describing Distributions with numbers

STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model

STAT Chapter 6 The Standard Deviation (SD) as a Ruler and The Normal Model

The Normal Probability Distribution

NOTES TO CONSIDER BEFORE ATTEMPTING EX 2C BOX PLOTS

Variance, Standard Deviation Counting Techniques

Handout 4 numerical descriptive measures part 2. Example 1. Variance and Standard Deviation for Grouped Data. mf N 535 = = 25

DATA HANDLING Five-Number Summary

Chapter 4 Variability

Applications of Data Dispersions

Frequency Distribution and Summary Statistics

CHAPTER 6 Random Variables

STA Module 3B Discrete Random Variables

Basic Procedure for Histograms

DATA SUMMARIZATION AND VISUALIZATION

Some Characteristics of Data

Chapter 6: Random Variables

Empirical Rule (P148)

Chapter 6: Random Variables

SOLUTIONS TO THE LAB 1 ASSIGNMENT

Chapter 3. Descriptive Measures. Copyright 2016, 2012, 2008 Pearson Education, Inc. Chapter 3, Slide 1

Discrete Probability Distribution

Much of what appears here comes from ideas presented in the book:

SECTION 6.2 (DAY 1) TRANSFORMING RANDOM VARIABLES NOVEMBER 16 TH, 2017

The Range, the Inter Quartile Range (or IQR), and the Standard Deviation (which we usually denote by a lower case s).

Found under MATH NUM

Description of Data I

AP Statistics Chapter 6 - Random Variables

Exploratory Data Analysis

MA131 Lecture 8.2. The normal distribution curve can be considered as a probability distribution curve for normally distributed variables.

MAT 1371 Midterm. This is a closed book examination. However one sheet is permitted. Only non-programmable and non-graphic calculators are permitted.

Lecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1

Section 6.2 Transforming and Combining Random Variables. Linear Transformations

SUMMARY STATISTICS EXAMPLES AND ACTIVITIES

5.1 Mean, Median, & Mode

Section 7.4 Transforming and Combining Random Variables (DAY 1)

STAB22 section 1.3 and Chapter 1 exercises

Unit 2: Statistics Probability

Measures of Dispersion (Range, standard deviation, standard error) Introduction

Chapter 3: Displaying and Describing Quantitative Data Quiz A Name

Stat 101 Exam 1 - Embers Important Formulas and Concepts 1

David Tenenbaum GEOG 090 UNC-CH Spring 2005

Introduction to Computational Finance and Financial Econometrics Descriptive Statistics

STA Rev. F Learning Objectives. What is a Random Variable? Module 5 Discrete Random Variables

Center and Spread. Measures of Center and Spread. Example: Mean. Mean: the balance point 2/22/2009. Describing Distributions with Numbers.

AP Stats ~ Lesson 6B: Transforming and Combining Random variables

Chapter 16. Random Variables. Copyright 2010 Pearson Education, Inc.

Math 243 Lecture Notes

Math 140 Introductory Statistics

Lecture 9. Probability Distributions. Outline. Outline

Chapter 2: Descriptive Statistics. Mean (Arithmetic Mean): Found by adding the data values and dividing the total by the number of data.

Numerical Descriptive Measures. Measures of Center: Mean and Median

CHAPTER 6 Random Variables

Statistics vs. statistics

Today s plan: Section 4.1.4: Dispersion: Five-Number summary and Standard Deviation.

CHAPTER 2 Describing Data: Numerical

Lecture 9. Probability Distributions

Econ 300: Quantitative Methods in Economics. 11th Class 10/19/09

I. Standard Error II. Standard Error III. Standard Error 2.54

2 DESCRIPTIVE STATISTICS

Math 2200 Fall 2014, Exam 1 You may use any calculator. You may not use any cheat sheet.

Mini-Lecture 3.1 Measures of Central Tendency

Overview/Outline. Moving beyond raw data. PSY 464 Advanced Experimental Design. Describing and Exploring Data The Normal Distribution

Quantitative Analysis and Empirical Methods

MATH FOR LIBERAL ARTS REVIEW 2

MAKING SENSE OF DATA Essentials series

The Normal Distribution

Edexcel past paper questions

Chapter 6: Random Variables

Since his score is positive, he s above average. Since his score is not close to zero, his score is unusual.

Review. What is the probability of throwing two 6s in a row with a fair die? a) b) c) d) 0.333

Random Variables. Note: Be sure that every possible outcome is included in the sum and verify that you have a valid probability model to start with.

UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences. STAB22H3 Statistics I Duration: 1 hour and 45 minutes

VARIABILITY: Range Variance Standard Deviation

Lecture 18 Section Mon, Feb 16, 2009

Percentiles, STATA, Box Plots, Standardizing, and Other Transformations

Transcription:

Math 140 Introductory Statistics First midterm September 23 2010

Box Plots Graphical display of 5 number summary Q1, Q2 (median), Q3, max, min

Outliers If a value is more than 1.5 times the IQR from the nearest quartile it may be an outlier Look at the speeds of the animals. Is the cheetah an outlier? Is the pig an outlier? Is the squirrel an outlier? Is the lion an outlier? Which animal is the largest non-outlier?

Outliers If a value is more than 1.5 times the IQR from the nearest quartile it may be an outlier Q1=30 Q2=37 Q3 =42

Outliers If a value is more than 1.5 times the IQR from the nearest quartile it may be an outlier IQR = 12 1.5*IQR = 18 Q3 + 1.5*IQR = 42+18 = 60 Q1-1.5*IQR = 30-18 = 12

Outliers IQR = 12 1.5*IQR = 18 Q3 + 1.5*IQR = 42+18 = 60 Q1-1.5*IQR = 30-18 = 12 Cheetah = 70 Pig = 11 Squirrel = 12 Lion = 50

Modified box plot Graphical display of 5 number summary Q1, Q2, Q3, max, min and outliers Modified box plot

Box plots Box Plots are useful when Plotting a single quantitative variable Want to compare shape, center, and spread of two or more distributions. The distribution has a large number of values Individual values do not need to be identified. We may want to identify outliers.

Spread - Deviation Deviation of a value x is how far it is from the mean x - x This value is different for every data point x and can be negative or positive

Standard deviation

Standard deviation Data 2, 7, 8, 12, 12, 19 n=? average x =? x 2 7 8 12 12 19 x-x (x-x) 2 total sum = 60

Standard deviation Find σ n and σ n-1

Standard deviation The square of the standard deviation is the variance

Standard deviation The standard deviation is considered to be the typical deviation from the mean The larger the SD, the more spread out the data is

What if we have a frequency table?

What if we have a frequency table? To calculate the mean we d have to sum 0+0+0+1+1+1+3+3+.. Or use the formula above

What if we have a frequency table? [(0*3) + (1*3) + (3*2) +.]/95

Recentering and Rescaling Recentering a data set Add the same number c to all values The shape or spread do not change. It slides the entire distribution by the amount c, adding c to the median and the mean. Rescaling a data set Multiply all values by the same positive number d The basic shape doesn t change. It stretches or shrinks the distribution, multiplying the spread (IQR or SD) by d and multiplying the center (median or mean) by d

Recentering and Rescaling Want to move to Celsius C = 5/9 (F-32)

Recentering original subtract 32

Rescaling original subtract 32 Multiply by 5/9

Rescaling original subtract 32 Multiply by 5/9

A problem for you Suppose a U.S. dollar is worth 14.5 Mexican pesos. a. A set of prices, in U.S. dollars, has mean $20 and standard deviation $5. Find the mean and standard deviation of the prices expressed in pesos. b. Another set of prices, in Mexican pesos, has a median of 145.0 pesos and quartiles of 72.5 pesos and 29 pesos. Find the median and quartiles of the same prices expressed in U.S. dollars.

The influence of outliers A summary statistic is resistant to outliers if it does not change very much when an outlier is removed. sensitive to outliers if the summary statistic is greatly affected by the removal of outliers.

The influence of outliers Viewers for the finale of the most popular TV shows Who are the outliers? How do mean and SD change if we remove them?

The influence of outliers

Normal distributions

Normal distributions The normal distribution tells us how averages and SD behave when you repeat a random process Nice property: A normal distribution is determined by its mean and standard deviation! (If you know mean and SD you know everything)

An example The distribution of the SAT scores for the University of Washington was roughly normal in shape, with mean 1055 and standard deviation 200. 1. What percentage of scores were 920 or below? 2. What SAT score separates the lowest 25% of the SAT scores from the rest?

An example The distribution of the SAT scores for the University of Washington was roughly normal in shape, with mean 1055 and standard deviation 200. 1. What percentage of scores were 920 or below? 2. What SAT score separates the lowest 25% of the SAT scores from the rest? We already know that 68% of data is between 855 and 1255

Unknown percentage problem 1. What percentage of scores were 920 or below? Given z (a score), find the percentage

Unknown value problem 2. What SAT score separates the lowest 25% of the scores from the rest? Given the percentage P, find the score z

Standard normal distribution The normal distribution with mean =0 and SD = 1

Standard normal distribution Any normal distribution can be rescaled or recentered to give you the normal distribution STANDARDIZING or CONVERTING TO STANDARD UNITS

Given the score z find P Unknown percentage Table A. Page 759 Use the units and the first decimal to locate the row and the closest hundredths digits to locate the column. The number found is the percentage of the number of value.

Hk Page 73, E49, E50, E51, E52, E55, E59, E60