{ Statistics Review One Semester in 50 minutes. Setting up a null- hypothesis and finding the p-value.

Slides:



Advertisements
Similar presentations
Testing a Claim about a Proportion Assumptions 1.The sample was a simple random sample 2.The conditions for a binomial distribution are satisfied 3.Both.
Advertisements

Hypothesis Testing A hypothesis is a claim or statement about a property of a population (in our case, about the mean or a proportion of the population)
Inference Sampling distributions Hypothesis testing.
STAT 135 LAB 14 TA: Dongmei Li. Hypothesis Testing Are the results of experimental data due to just random chance? Significance tests try to discover.
The Structure of a Hypothesis Test. Hypothesis Testing Hypothesis Test Statistic P-value Conclusion.
Objectives Use simulations and hypothesis testing to compare treatments from a randomized experiment.
Chapter 10: Hypothesis Testing
Significance Testing Chapter 13 Victor Katch Kinesiology.
Stat 301 – Day 17 Tests of Significance. Last Time – Sampling cont. Different types of sampling and nonsampling errors  Can only judge sampling bias.
Stat 301 – Day 19 One sample z-test (4.3). Last Week - Sampling How to select random samples so that we feel comfortable generalizing from our sample.
Stat Day 16 Observations (Topic 16 and Topic 14)
LARGE SAMPLE TESTS ON PROPORTIONS
Hypothesis Tests for Means The context “Statistical significance” Hypothesis tests and confidence intervals The steps Hypothesis Test statistic Distribution.
Stat 512 – Day 8 Tests of Significance (Ch. 6). Last Time Use random sampling to eliminate sampling errors Use caution to reduce nonsampling errors Use.
8-2 Basics of Hypothesis Testing
8-3 Testing a Claim about a Proportion
Copyright © 2014, 2013, 2010 and 2007 Pearson Education, Inc. Chapter Hypothesis Tests Regarding a Parameter 10.
Stat 217 – Day 15 Statistical Inference (Topics 17 and 18)
BCOR 1020 Business Statistics Lecture 18 – March 20, 2008.
Chapter 9 Hypothesis Testing.
BCOR 1020 Business Statistics
Definitions In statistics, a hypothesis is a claim or statement about a property of a population. A hypothesis test is a standard procedure for testing.
Section 7-2 Hypothesis Testing for the Mean (n  30)
Normal and Sampling Distributions A normal distribution is uniquely determined by its mean, , and variance,  2 The random variable Z = (X-  /  is.
Copyright ©2005 Brooks/Cole, a division of Thomson Learning, Inc. Rejecting Chance – Testing Hypotheses in Research Chapter 22.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 9 Hypothesis Testing.
Estimation and Hypothesis Testing. The Investment Decision What would you like to know? What will be the return on my investment? Not possible PDF for.
The smokers’ proportion in H.K. is 40%. How to testify this claim ?
Chapter 8 Hypothesis testing 1. ▪Along with estimation, hypothesis testing is one of the major fields of statistical inference ▪In estimation, we: –don’t.
STATISTICAL INFERENCE PART VII
Inference for a Single Population Proportion (p).
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Hypothesis Testing for Proportions
Chapter 9: Hypothesis Testing 9.1 Introduction to Hypothesis Testing Hypothesis testing is a tool you use to make decision from data. Something you usually.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved Section 8-3 Testing a Claim About a Proportion.
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Testing a Claim about a Proportion Section 7-5 M A R I O F. T R I O L A Copyright.
Hypothesis Testing State the hypotheses. Formulate an analysis plan. Analyze sample data. Interpret the results.
1 Chapter 8 Hypothesis Testing 8.2 Basics of Hypothesis Testing 8.3 Testing about a Proportion p 8.4 Testing about a Mean µ (σ known) 8.5 Testing about.
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Example 10.17:
Copyright © 2010, 2007, 2004 Pearson Education, Inc Section 8-2 Basics of Hypothesis Testing.
Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.
McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 8 Hypothesis Testing.
Chapter 221 What Is a Test of Significance?. Chapter 222 Thought Question 1 The defendant in a court case is either guilty or innocent. Which of these.
PSY 307 – Statistics for the Behavioral Sciences Chapter 9 – Sampling Distribution of the Mean.
Introduction to Inference: Confidence Intervals and Hypothesis Testing Presentation 8 First Part.
Unit 8 Section 8-3 – Day : P-Value Method for Hypothesis Testing  Instead of giving an α value, some statistical situations might alternatively.
Chapter 11 Inferences about population proportions using the z statistic.
Rejecting Chance – Testing Hypotheses in Research Thought Questions 1. Want to test a claim about the proportion of a population who have a certain trait.
Logic and Vocabulary of Hypothesis Tests Chapter 13.
Welcome to MM570 Psychological Statistics
Testing Hypotheses about a Population Proportion Lecture 29 Sections 9.1 – 9.3 Fri, Nov 12, 2004.
Business Statistics for Managerial Decision Farideh Dehkordi-Vakil.
© Copyright McGraw-Hill 2004
Introduction to Hypothesis Testing
Aim: What is the P-value method for hypothesis testing? Quiz Friday.
1 Definitions In statistics, a hypothesis is a claim or statement about a property of a population. A hypothesis test is a standard procedure for testing.
Section 10.2: Tests of Significance Hypothesis Testing Null and Alternative Hypothesis P-value Statistically Significant.
Major Steps. 1.State the hypotheses.  Be sure to state both the null hypothesis and the alternative hypothesis, and identify which is the claim. H0H0.
Welcome to MM207 Unit 7 Seminar Dr. Bob Hypothesis Testing and Excel 1.
Hypothesis Testing and Statistical Significance
Confidence Intervals and Hypothesis Tests Week 5.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. 1 FINAL EXAMINATION STUDY MATERIAL III A ADDITIONAL READING MATERIAL – INTRO STATS 3 RD EDITION.
© 2010 Pearson Prentice Hall. All rights reserved Chapter Hypothesis Tests Regarding a Parameter 10.
9.3 Hypothesis Tests for Population Proportions
Hypothesis Testing for Proportions
Hypothesis Testing for Proportions
Two-sided p-values (1.4) and Theory-based approaches (1.5)
Section 10.2: Tests of Significance
Chapter 18 The Binomial Test
Statistical Test A test of significance is a formal procedure for comparing observed data with a claim (also called a hypothesis) whose truth we want to.
Presentation transcript:

{ Statistics Review One Semester in 50 minutes

Setting up a null- hypothesis and finding the p-value.

QUESTION: Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? (Investigation 1)

How would we answer this question?

QUESTION: Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? Philosophy: Lets gather a bunch of data and find out how surprising our results are.

1.We write a null hypothesis: the null hypothesis is the boring (“status-quo”) hypothesis that we want to show is unlikely to be true given our data. Process:

1.We write a null hypothesis: the null hypothesis is the boring (“status-quo”) hypothesis that we want to show is unlikely to be true given our data. 2.The alternative hypothesis is our research question. We are hoping to reject the null hypothesis in favor of the alternative hypothesis. Process:

1.We write a null hypothesis: the null hypothesis is the boring (“status-quo”) hypothesis that we want to show is unlikely to be true given our data. 2.The alternative hypothesis is our research question. We are hoping to reject the null hypothesis in favor of the alternative hypothesis. 3.Gather data Process:

1.We write a null hypothesis: the null hypothesis is the boring (“status-quo”) hypothesis that we want to show is unlikely to be true given our data. 2.The alternative hypothesis is our research question. We are hoping to reject the null hypothesis in favor of the alternative hypothesis. 3.Gather data 4.Do stats (to determine whether we can reject the null hypothesis) Process:

Do Stats Can we reject the null hypothesis? Method: 1.Assume the null hypothesis is true. 2.Calculate the probability of getting results as (or more) extreme than the data given that null hypothesis is true. 3.If we are unlikely (usually use less than 5% probability) to get these extreme results, then we reject the null-hypothesis. Otherwise we do not reject it.

Note: This method only works one-way. If we reject the null hypothesis than we claim that the alternative hypothesis is true (this is what researchers want the result to be). If we do NOT reject the null hypothesis we CANNOT claim anything.

2. Calculating the probability of getting results as (or more) extreme than the data given that null hypothesis is true. -this probability is the p-value! (which you all know since we memorized it for the last exam). In other words: are our results different enough from what we would expect (assuming null hypothesis is true) to conclude that the null hypothesis is not true?

Example: (Investigation 1) – Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? Null Hypothesis State the null hypothesis in english (no numbers or symbols): (class) State the null hypothesis mathematically: (class)

Example: (Investigation 1) – Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? Null Hypothesis State the null hypothesis in english (no numbers or symbols): The video doesn’t affect the baby’s choice. Baby is equally likely to pick either toy. State the null hypothesis mathematically: H_0: p=0.5(p is the probability of choosing the good toy)

Example: (Investigation 1) – Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? Alternative Hypothesis State the alternative hypothesis in english (no numbers or symbols): class State the alternative hypothesis mathematically: class

Example: (Investigation 1) – Are babies more likely to pick the “good” toy then the “bad” toy after watching a video? Alternative Hypothesis State the alternative hypothesis in english (no numbers or symbols): The video does affect the baby’s choice. Baby is more likely to pick the good toy. State the alternative hypothesis mathematically: H_a: p>0.5 (when would we use not equal??)

Data: We collected data on 16 babies and found that 14 of them picked the “good” toy. When calculating the p-value what is our parameter? 1.A mean 2.The difference between two means 3.A proportion 4.The difference between two proportions 5.Your mom

Data: We collected data on 16 babies and found that 14 of them picked the “good” toy. When calculating the p-value what is our parameter? 1.A mean 2.The difference between two means 3.A proportion 4.The difference between two proportions 5.Your mom *we could think of it as a mean – the number of babies picking the good toy, or the proportion of babies who pick the good toy.

Data: We collected data on 16 babies and found that 14 of them picked the “good” toy. How do we find the p-value?? 1.Use a z-statistic?? 2.Use a t-statistic?? 3.Use the applet (or another simulation)?? 4.Calculate the exact probability?? Why??

Data: We collected data on 16 babies and found that 14 of them picked the “good” toy. How do we find the p-value?? 1.Use a z-statistic?? 2.Use a t-statistic?? 3.Use the applet (or another simulation)?? –OK but only gives us an approximation 4.Calculate the exact probability?? This gives us the exact p-value for this problem. But how do we do this?? Why??

3. Use the applet (or another simulation) to approximate the p-value Flip a fair coin 16 times. Did we get 14, 15, 16 heads? (this is “as or more extreme than the data”) Repeat this process MANY times. What proportion of times did we get these extreme results (14,15,16 heads)

Simulation results with 1000 trials of 16 flips histogram

( number of times we flipped 14 Heads PLUS number of times we flipped 15 Heads PLUS number of times we flipped 16 Heads) divided by total number of trials (3+2+0)/1000=5/1000=.005 P-value is approximately:

( number of times we flipped 14 Heads PLUS number of times we flipped 15 Heads PLUS number of times we flipped 16 Heads) divided by total number of flips (3+2+0)/1000=5/1000=.005 P-value is approximately: There is (approximately) a chance (0.5%) that we would get 14 or more Heads if the null hypothesis is true. VERY UNLIKELY. So we reject the null hypothesis and conclude that the alternative hypothesis is true. The area of the right 3 rectangles ->

4. Calculate the exact probability. How??

Calculate the exact probability. P-value=P(14 Heads)+P(15 Heads)+P(16 Heads) How do we calculate this?

Calculate the exact probability. P-value=P(14 Heads)+P(15 Heads)+P(16 Heads) How do we calculate this? Binomial Theorem!!

Now: What if we collected data on 100 babies (instead of 16)?? What would change??

Data: We collected data on 100 babies and found that 61 of them picked the “good” toy. How do we find the p-value?? 1.Use a z-statistic?? 2.Use a t-statistic?? 3.Use the applet (or another simulation)?? 4.Calculate the exact probability?? Why??

Data: We collected data on 100 babies and found that 61 of them picked the “good” toy. How do we find the p-value?? 1.Use a z-statistic?? 2.Use a t-statistic?? 3.Use the applet (or another simulation)?? 4.Calculate the exact probability?? (3) and (4): this gets tougher as our sample size (n) gets larger.

“Exact” Probabilities For n large (np>15 and nq>15 ish) this looks like normal curve. So if we transform it into a “Standard Normal”, we can use the Normal Table to approximate the area (p-value)

How do we transform a Normal Distribution with mean μ and standard deviation into a standard normal?? What is the mean and standard deviation of a standard normal?

How do we transform a Normal Distribution with mean μ and standard deviation into a standard normal?? What is the mean and standard deviation of a standard normal? Find the z-score (number of standard deviations larger than the mean). Standard Normal has mean 0 and standard deviation 1.

Z-score on board