Test for Goodness of Fit. The math department at a community college offers 3 classes that satisfy the math requirement for transfer in majors that do.

Slides:



Advertisements
Similar presentations
Finish Anova And then Chi- Square. Fcrit Table A-5: 4 pages of values Left-hand column: df denominator df for MSW = n-k where k is the number of groups.
Advertisements

Chapter 12 Goodness-of-Fit Tests and Contingency Analysis
Chi-Squared Tutorial This is significantly important. Get your AP Equations and Formulas sheet.
Chapter 10 Chi-Square Tests and the F- Distribution 1 Larson/Farber 4th ed.
© 2010 Pearson Prentice Hall. All rights reserved The Chi-Square Test of Homogeneity.
PSY 340 Statistics for the Social Sciences Chi-Squared Test of Independence Statistics for the Social Sciences Psychology 340 Spring 2010.
Chapter 11 Chi-Square Procedures 11.1 Chi-Square Goodness of Fit.
Probability & Statistics for Engineers & Scientists, by Walpole, Myers, Myers & Ye ~ Chapter 10 Notes Class notes for ISE 201 San Jose State University.
11-2 Goodness-of-Fit In this section, we consider sample data consisting of observed frequency counts arranged in a single row or column (called a one-way.
11-3 Contingency Tables In this section we consider contingency tables (or two-way frequency tables), which include frequency counts for categorical data.
P-value Method 2 means, sigmas unknown. Sodium levels are measured in millimoles per liter (mmol/L) and a score between 136 and 145 is considered normal.
Traditional Method 2 means, σ’s known. The makers of a standardized exam have two versions of the exam: version A and version B. They believe the two.
Chi-Square Tests and the F-Distribution
P-value Method One Mean, sigma known. The average length of a certain insect has been determined to be.52 cm with a standard deviation of.03 cm. A researcher.
Traditional Method 2 means, dependent samples. A data entry office finds itself plagued by inefficiency. In an attempt to improve things the office manager.
Traditional Method 2 proportions. The President of a homeowners’ association believes that pink flamingos on lawns are tacky, or as she puts it, “detrimental.
P-value method 1 mean, σ unknown. A student claims that the average statistics textbook has fewer than 650 pages. In a sample of 52 statistics texts,
One-way Analysis of Variance (ANOVA) Note: In this version, we’ll use Excel to do all the calculations. If you wanted the tutorial that worked through.
P-value method 2 means, both σ’s known. An economist is comparing credit card debt from two recent years. She has gathered the following data: Year 1.
P-value Method 2 proportions. A resident of a small housing complex has a pet monkey who likes to sit out on the porch and smoke cigarettes. Some of the.
P-value method dependent samples. A group of friends wants to compare two energy drinks. They agree to meet on consecutive Saturdays to run a mile. One.
P-value method One Proportion. The mayor of Pleasantville has just signed a contract allowing a biohazards company to build a waste disposal site on what.
Traditional Method One mean, sigma known. The Problem In 2004, the average monthly Social Security benefit for retired workers was $ with a standard.
Traditional Method One Proportion. A researcher claims that the majority of the population supports a proposition raising taxes to help fund education.
Traditional method 2 means, σ’s unknown. Scientists studying the effect of diet on cognitive ability are comparing two groups of mice. The first group.
Hypothesis Testing:.
Chi-squared Testing for a difference. What does it do? Compares numbers of people/plants/species… in different categories (eg different pollution levels,
Chi-squared Goodness of fit. What does it do? Tests whether data you’ve collected are in line with national or regional statistics.  Are there similar.
Traditional Method 1 mean, sigma unknown. In a national phone survey conducted in May 2012, adults were asked: Thinking about social issues, would you.
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 10.7.
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 10.3.
Section 10.1 Goodness of Fit. Section 10.1 Objectives Use the chi-square distribution to test whether a frequency distribution fits a claimed distribution.
Chapter 11: Applications of Chi-Square. Count or Frequency Data Many problems for which the data is categorized and the results shown by way of counts.
AP Statistics Chapter 26 Notes
Copyright © 2010, 2007, 2004 Pearson Education, Inc. 1.. Section 11-2 Goodness of Fit.
10.1: Multinomial Experiments Multinomial experiment A probability experiment consisting of a fixed number of trials in which there are more than two possible.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Chapter 10 Chi-Square Tests and the F-Distribution
Copyright © 2005 Brooks/Cole, a division of Thomson Learning, Inc Chapter 16 Chi-Squared Tests.
GOODNESS OF FIT Larson/Farber 4th ed 1 Section 10.1.
Warm up On slide.
Other Chi-Square Tests
Chi-Square Test James A. Pershing, Ph.D. Indiana University.
Copyright © 2010 Pearson Education, Inc. Slide
Section 10.2 Independence. Section 10.2 Objectives Use a chi-square distribution to test whether two variables are independent Use a contingency table.
© Copyright McGraw-Hill CHAPTER 11 Other Chi-Square Tests.
Reasoning in Psychology Using Statistics Psychology
Copyright © Cengage Learning. All rights reserved. Chi-Square and F Distributions 10.
11.2 Tests Using Contingency Tables When data can be tabulated in table form in terms of frequencies, several types of hypotheses can be tested by using.
Statistics 300: Elementary Statistics Section 11-2.
Outline of Today’s Discussion 1.The Chi-Square Test of Independence 2.The Chi-Square Test of Goodness of Fit.
Chi-Square Test (χ 2 ) χ – greek symbol “chi”. Chi-Square Test (χ 2 ) When is the Chi-Square Test used? The chi-square test is used to determine whether.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
+ Section 11.1 Chi-Square Goodness-of-Fit Tests. + Introduction In the previous chapter, we discussed inference procedures for comparing the proportion.
Chi-squared Association Index. What does it do? Looks for “links” between two factors  Do dandelions and plantains tend to grow together?  Does the.
Statistics 300: Elementary Statistics Section 11-3.
Lesson Runs Test for Randomness. Objectives Perform a runs test for randomness Runs tests are used to test whether it is reasonable to conclude.
Section 10.2 Objectives Use a contingency table to find expected frequencies Use a chi-square distribution to test whether two variables are independent.
Section 7.3 Hypothesis Testing for the Mean (Small Samples) © 2012 Pearson Education, Inc. All rights reserved. 1 of 15.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Section 10.1 Goodness of Fit © 2012 Pearson Education, Inc. All rights reserved. 1 of 91.
Hypothesis Testing for Means (Small Samples)
10 Chapter Chi-Square Tests and the F-Distribution Chapter 10
Chapter 7 Hypothesis Testing with One Sample.
Hypothesis Testing for Population Means (s Unknown)
Section 10-1 – Goodness of Fit
1) A bicycle safety organization claims that fatal bicycle accidents are uniformly distributed throughout the week. The table shows the day of the week.
MATH 2311 Section 8.5.
Presentation transcript:

Test for Goodness of Fit

The math department at a community college offers 3 classes that satisfy the math requirement for transfer in majors that do not require calculus: College Algebra, Statistics, and Finite Math*. At Saddleback College, we no longer offer Finite Math, as this course proved to be significantly less popular than the other two. College Algebra Statistics Finite Math

The math department chair is trying to determine how many sections of each class to offer. She claims that students show no preference for which class they take; if this proves to be so she will offer equal numbers of each class. She looks at the number of students who enrolled in each class during the previous semester. College Algebra students Statistics students Finite Math students

She finds the following data: College AlgebraStatisticsFinite Math # students enrolled Determine whether it is reasonable to suppose students have no preference between the three classes (and thus to offer the same number of sections of each.) Use the goodness-of-fit test with α =.05.

If you’d like to try this problem on your own and just check your answer when you’re done go ahead. When you’re ready to check your answer click on the genius to the right. If you’d rather work through this problem together click away from the genius or hit the space bar or forward arrow key.

Set-up The table tells us the observed frequency. College AlgebraStatisticsFinite Math # students enrolled (Observed frequency) It’s our job to calculate the expected frequency.

College AlgebraStatisticsFinite Math # students enrolled (Observed frequency) Expected frequency

To do this, we’ll need to calculate the total number of students enrolled in all three classes. College AlgebraStatisticsFinite Math # students enrolled (Observed frequency) Expected frequency

To do this, we’ll need to calculate the total number of students enrolled in all three classes. College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency

To do this, we’ll need to calculate the total number of students enrolled in all three classes. College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency

Now we can calculate the expected frequency. If the students have no preference between the three classes, we would expect the students to be equally distributed between them. College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency Divide the total number of students by 3, the number of classes they can choose from.

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360

Step 1: State the hypotheses and identify the claim (if there is one). The claim is that the students have no preference---there’s no math symbol for this, so we’ll just say it in words.

Eeny, meeny, miney, moe Algebra Stat Finite This is the Null since the Null always states there is no difference between things. We care!

Step (*) Draw the chi-square distribution and label the area in the right tail. Can we use this distribution?

Since all the expected frequencies are at least 5, we can use the chi-square distribution!

.05 Remember, the chi-square test is always right- tailed. (In this case, so is the bull.)

Step 2: Mark off the critical value..05 The critical value is the boundary of the right tail. It will go here.

Any time we use the Chi-square distribution, we need to use table G. Remember that the degrees of freedom will be one less than the number of categories (in this case, the number of classes.)

College Algebra Statistics Finite Math Since there were 3 classes, the degrees of freedom is 3-1 = 2

So we look in the row for d.f. = 2. And the column for α = The critical value is

Let’s add this to the picture

Step 3: Calculate the test value.

sum observed frequency expected frequency College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360 Refer back to this table to find the observed and expected frequencies

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360

College Algebra StatisticsFinite MathTotal # students enrolled (Observed frequency) Expected frequency 360

Now add the test value to the picture is (much) bigger than 5.991, so it goes to the right.

Step 4: Make the decision The test value is in the critical region. Reject the Null!

RATS! Rejected again! We rats had nothing to do with it.

Step 5: Answer the question in plain English. There is enough evidence to reject the claim that students have no preference among the three math classes.

Here’s a quick summary …

Each click will show you one step. Step (*) is broken up into two clicks. Step 1 Step (*) Step Step 3 Step 4 Reject the Null. Step 5 There is enough evidence to reject the claim that the students have no preference among the three classes.

And there was much rejoicing