Section 1.2 Continued Discrimination in the Workplace: Inference through Simulation: Discussion.

Slides:



Advertisements
Similar presentations
AP Statistics Introduction to Elementary Statistical Methods
Advertisements

Estimating a Population Mean
Chapter 12: Testing hypotheses about single means (z and t) Example: Suppose you have the hypothesis that UW undergrads have higher than the average IQ.
Hypothesis Testing making decisions using sample data.
Chapter 10: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 10: Estimating with Confidence
Warm-up 5.1 Introduction to Probability 1) 2) 3) 4) 5) 6) 7)
Chapter 3 Producing Data 1. During most of this semester we go about statistics as if we already have data to work with. This is okay, but a little misleading.
Chapter 10: Estimating with Confidence
Sampling Methods.
Section 1.2 Discrimination in the Workplace: Inference through Simulation.
Section 1.1 Discrimination in the Workplace: Data Exploration.
A P STATISTICS LESSON 9 – 1 ( DAY 1 ) SAMPLING DISTRIBUTIONS.
Math 227 Elementary Statistics
9.1 – Sampling Distributions. Many investigations and research projects try to draw conclusions about how the values of some variable x are distributed.
CHAPTER 8 Estimating with Confidence
Chapter 8 Introduction to Inference Target Goal: I can calculate the confidence interval for a population Estimating with Confidence 8.1a h.w: pg 481:
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.1 Confidence Intervals: The.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.1 Confidence Intervals: The.
+ Warm-Up4/8/13. + Warm-Up Solutions + Quiz You have 15 minutes to finish your quiz. When you finish, turn it in, pick up a guided notes sheet, and wait.
90288 – Select a Sample and Make Inferences from Data The Mayor’s Claim.
90288 – Select a Sample and Make Inferences from Data The Mayor’s Claim.
Lesson Comparing Two Proportions. Knowledge Objectives Identify the mean and standard deviation of the sampling distribution of p-hat 1 – p-hat.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Unit 5: Hypothesis Testing.
Section Using Simulation to Estimate Probabilities Objectives: 1.Learn to design and interpret simulations of probabilistic situations.
Day 3: Sampling Distributions. CCSS.Math.Content.HSS-IC.A.1 Understand statistics as a process for making inferences about population parameters based.
Chapter 7 Sampling Distributions Statistics for Business (Env) 1.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Unit 5: Estimating with Confidence Section 10.1 Confidence Intervals: The Basics.
Statistics 101 Chapter 10 Section 2. How to run a significance test Step 1: Identify the population of interest and the parameter you want to draw conclusions.
6.1 Inference for a Single Proportion  Statistical confidence  Confidence intervals  How confidence intervals behave.
+ DO NOW. + Chapter 8 Estimating with Confidence 8.1Confidence Intervals: The Basics 8.2Estimating a Population Proportion 8.3Estimating a Population.
Warm-up 1.2 Introduction to Summary Statistics and Simulation 1.What percentage of recent hires are older than 50? 2.What percentage of hourly recent hires.
1 Chapter 9: Sampling Distributions. 2 Activity 9A, pp
Essential Questions How do we use simulations and hypothesis testing to compare treatments from a randomized experiment?
5.2 Using Simulation to Estimate Probabilities HW: E’s 15, 17, 19, 21.
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Unit 5: Hypothesis Testing.
Uncertainty and confidence Although the sample mean,, is a unique number for any particular sample, if you pick a different sample you will probably get.
The inference and accuracy We learned how to estimate the probability that the percentage of some subjects in the sample would be in a given interval by.
Hypothesis Tests for 1-Proportion Presentation 9.
Chapter 8: Estimating with Confidence
+ The Practice of Statistics, 4 th edition – For AP* STARNES, YATES, MOORE Chapter 8: Estimating with Confidence Section 8.1 Confidence Intervals: The.
Slope (b) = Correlation (r) = Slope (b) = Correlation (r) = WARM UP 1.Perform a Linear Regression on the following points and.
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Unit 5 – Chapters 10 and 12 What happens if we don’t know the values of population parameters like and ? Can we estimate their values somehow?
What Is a Test of Significance?
Unit 5: Hypothesis Testing
AP Statistics Introduction to Elementary Statistical Methods Mr. Kent
Daniela Stan Raicu School of CTI, DePaul University
Significance Tests: The Basics
Section 9.1 Significance Tests: The Basics
Significance Tests: The Basics
Chapter 8: Estimating with Confidence
WARM UP: Solve the equation for height for an age of 25.
Testing Hypotheses about a Population Proportion
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Chapter 8: Estimating with Confidence
Objectives 6.1 Estimating with confidence Statistical confidence
Samples and Populations
AP Statistics Introduction to Elementary Statistical Methods Mr. Kent
Presentation transcript:

Section 1.2 Continued Discrimination in the Workplace: Inference through Simulation: Discussion

 Average age 48.6  Ten workers were selected from 14, so to simulate this we would:  List the 14 ages and assign numbers  Select 10 different employees randomly from the group using random integers.  Find the average of these 10 ages.  Repeat these steps many times.  Create a dot plot of the averages.  This can then be used to calculate the proportion or probability of randomly selecting 10 employees of an average age within a certain range.

 The average was of 200 dots are above 48.6 for a proportion of  Meaning that the probability of getting an average age of 48.6 or higher in a single trial is 22.5%.  This evidence would not help support Mr. Martin’s case. It would mean we would expect this to happen by chance 22.5% of the time, which is a reasonable chance and not a rare occurence.

 Approximate dot plot:  Explain why we consider looking at the probability (proportion) of a range of values instead of a specific value.  Each individual value may or may not even appear, so it is difficult to estimate a probability at a specific value.

 Create a classroom Dot Plot of your averages for each repetition.  Look at the Dot Plot: How many times did we get a result of 58 or higher?  Based on our simulation, what is the probability that you would randomly get an average age of 58 or higher?  Probability: proportion of successes out of total trials in the long run.  If Westvaco was truly unbiased by age would you expect that they chose the people they did? Explain.

 If we decided that the probability was high enough that there was reasonable possibility that Westvaco could have chosen those employees without bias, then they may be off the hook.  However, if the probability was very low, we can say that it is very unlikely that they chose those employees unbiased of age.  They may still have valid reasoning, but now the need for an explanation is on them.

 Our overall probability of getting a 3 person average age of 58 or older for the day was about 2-6%. What does this mean to us?  If we truly selected 3 employees by some other means that did not have anything to do with age, the average age would be 58 or higher approx. 4% of the time.  In one round of layoffs, there is a 3-6% chance of having an average age of 58 or higher.  Is that significant enough to support Mr. Martin’s case for age discrimination?  Note: It is typical for a court to require or 2.5% or less for it to be considered truly significant enough to reject that it happened by chance.

 What is some key information you can get from summary tables?  Actual counts of certain characteristics within cases.  Maybe most importantly, the proportions of characteristics within cases. CasesA’sB’sTotal Female7916 Male51015 Total121931

 Consider the following information:  The number of violent crimes in a particular city has risen over the past 10 years; in 1995 the police documented 437 violent crimes, whereas in 2005 there were a total of 541 documented violent crimes.  Is this data sufficient to draw a reasonable conclusion regarding the level of change in violent crime? Explain  Not really…we don’t know the change in the population of the city.  If we did, a proportion of violent crime to population would be useful.

 Page 17 P4  Page 18 E9, E12, E13  On E9 you may use a Calculator simulation instead of slips of paper.  Be sure to answer questions completely with the context of the situation as the focus.