Prime of an NBA Career Cooper Handelsman. Research Question Is the prime of an NBA player at age 27? Has this prime changed over the last thirty years?

Slides:



Advertisements
Similar presentations
Four girls soccer teams took a random sample of players regarding the number of goals scored per game. The results are below. Use a significance level.
Advertisements

Ch. 21 Practice.
Model Adequacy Checking in the ANOVA Text reference, Section 3-4, pg
MARE 250 Dr. Jason Turner Analysis of Variance (ANOVA)
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Analysis of variance (ANOVA)-the General Linear Model (GLM)
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Differences Between Group Means
Chapter Topics The Completely Randomized Model: One-Factor Analysis of Variance F-Test for Difference in c Means The Tukey-Kramer Procedure ANOVA Assumptions.
MARE 250 Dr. Jason Turner Analysis of Variance (ANOVA) II.
Analysis of Variance (ANOVA) MARE 250 Dr. Jason Turner.
Lecture 9: One Way ANOVA Between Subjects
Chapter 2 Simple Comparative Experiments
Student’s t statistic Use Test for equality of two means
15-1 Introduction Most of the hypothesis-testing and confidence interval procedures discussed in previous chapters are based on the assumption that.
Nonparametric and Resampling Statistics. Wilcoxon Rank-Sum Test To compare two independent samples Null is that the two populations are identical The.
REGRETFUL SIGNINGS? BY: KEVIN PHILLIPS NONPARAMETRICS HARTLAUB.
Means Tests Hypothesis Testing Assumptions Testing (Normality)
1 Chapter 15: Nonparametric Statistics Section 15.1 How Can We Compare Two Groups by Ranking?
NONPARAMETRIC STATISTICS
© Buddy Freeman, 2015 H 0 : H 1 : α = Decision Rule: If then do not reject H 0, otherwise reject H 0. Test Statistic: Decision: Conclusion: We have found.
Independent samples- Wilcoxon rank sum test. Example The main outcome measure in MS is the expanded disability status scale (EDSS) The main outcome measure.
1 Design of Engineering Experiments Part 2 – Basic Statistical Concepts Simple comparative experiments –The hypothesis testing framework –The two-sample.
Introduction to Statistical Inference Probability & Statistics April 2014.
Introduction to SAS Essentials Mastering SAS for Data Analytics
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
A Comparison of Statistical Significance Tests for Information Retrieval Evaluation CIKM´07, November 2007.
TAUCHI – Tampere Unit for Computer-Human Interaction ERIT 2015: Data analysis and interpretation (1 & 2) Hanna Venesvirta Tampere Unit for Computer-Human.
Chapter 14 Nonparametric Statistics. 2 Introduction: Distribution-Free Tests Distribution-free tests – statistical tests that don’t rely on assumptions.
Lesson Inferences about the Differences between Two Medians: Dependent Samples.
Nonparametric Statistics aka, distribution-free statistics makes no assumption about the underlying distribution, other than that it is continuous the.
© Copyright McGraw-Hill CHAPTER 13 Nonparametric Statistics.
Hypothesis Testing A procedure for determining which of two (or more) mutually exclusive statements is more likely true We classify hypothesis tests in.
Nonparametric Statistics. In previous testing, we assumed that our samples were drawn from normally distributed populations. This chapter introduces some.
Nonparametric Tests IPS Chapter 15 © 2009 W.H. Freeman and Company.
HYPOTHESIS TESTING FRAMEWORK Farrokh Alemi Ph.D..
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 13 Multiple Regression Section 13.3 Using Multiple Regression to Make Inferences.
Lesson 15 - R Chapter 15 Review. Objectives Summarize the chapter Define the vocabulary used Complete all objectives Successfully answer any of the review.
STATISTICAL ANALYSIS FOR THE MATHEMATICALLY-CHALLENGED Associate Professor Phua Kai Lit School of Medicine & Health Sciences Monash University (Sunway.
Chapter 15 – Analysis of Variance Math 22 Introductory Statistics.
© Buddy Freeman, 2015 H 0 : H 1 : α = Decision Rule: If then do not reject H 0, otherwise reject H 0. Test Statistic: Decision: Conclusion: We have found.
Chapter 8 1-Way Analysis of Variance - Completely Randomized Design.
Nonparamentric Stats –Distribution free tests –e.g., rank tests Sign test –H 0 : Median = 100 H a : Median > 100 if median = 100, then half above, half.
Nonparametric Statistical Methods. Definition When the data is generated from process (model) that is known except for finite number of unknown parameters.
Logic and Vocabulary of Hypothesis Tests Chapter 13.
Hypothesis Testing Errors. Hypothesis Testing Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean.
NON-PARAMETRIC STATISTICS
The t-test: When you use it When you wish to compare the difference between two groups for a continuous (or discrete) variable Examples Blood pressure.
Nonparametric Statistics
MARE 250 Dr. Jason Turner Analysis of Variance (ANOVA)
Biostatistics Nonparametric Statistics Class 8 March 14, 2000.
Stats/Methods II JEOPARDY. Jeopardy Chi-Square Single-Factor Designs Factorial Designs Ordinal Data Surprise $100 $200$200 $300 $500 $400 $300 $400 $300.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
Comparing Two Proportions. AP Statistics Chap 13-2 Two Population Proportions The point estimate for the difference is p 1 – p 2 Population proportions.
One-way ANOVA Example Analysis of Variance Hypotheses Model & Assumptions Analysis of Variance Multiple Comparisons Checking Assumptions.
Nonparametric Tests with Ordinal Data Chapter 18.
Copyright © 2010, 2007, 2004 Pearson Education, Inc Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Analysis of variance Tron Anders Moger
Chapters Way Analysis of Variance - Completely Randomized Design.
Lesson Test to See if Samples Come From Same Population.
Area Test for Observations Indexed by Time L. B. Green Middle Tennessee State University E. M. Boczko Vanderbilt University.
MARE 250 Dr. Jason Turner Analysis of Variance (ANOVA)
 Kolmogor-Smirnov test  Mann-Whitney U test  Wilcoxon test  Kruskal-Wallis  Friedman test  Cochran Q test.
Nonparametric Statistics Overview. Objectives Understand Difference between Parametric and Nonparametric Statistical Procedures Nonparametric methods.
1 Underlying population distribution is continuous. No other assumptions. Data need not be quantitative, but may be categorical or rank data. Very quick.
The Differences in Ticket Prices for Broadway Shows By Courtney Snow I wanted to find out whether there was a significant difference in the price of musicals,
Team Payrolls... Yay, or nay?. Our Question We were curious: Do teams with one player occupying a large percentage of payroll win more games than other.
Nonparametric Statistics Overview
Do you know population SD? Use Z Test Are there only 2 groups to
Presentation transcript:

Prime of an NBA Career Cooper Handelsman

Research Question Is the prime of an NBA player at age 27? Has this prime changed over the last thirty years?

Subjects 38 participants in total 3 different draft classes: 1979, 1989, 1990 Must have played in every season from age 24-30

Statistics Four different statistics: PER, PPG, APG, RPG To find the peak, there are two different methods – Fitted line plot with quadratic model – Picking the best season

Tests Five test were run in order to test hypothesis – For the prime of the career: 1-sample t-test Wilcoxon signed rank – For the differences between decades: 1-sample ANOVA Kruskal-Wallis Multiple Comparisons (Steel-Dwass-Critchlow-Fligner )

1-sample t-test Procedure done 8 times H 0 : μ = 27 vs. H 1 : μ ≠27. t statistics: to P-values: 0.00 to Reject the null for all tests, mean is significantly different than 27

Wilcoxon Signed-rank Performed 8 times H 0 : θ=0 vs. H 1 : θ≠0 Wilcoxon test statistics: 68.5 to 117 P-values: 0.0 to.028 Reject the null for all tests, the median is significantly different from 27

Confidence Intervals

Differences Between the Decades Three decades represented: 1980, 1990, 2000 Peak is not important, it is just comparing the peaks regardless of what it is ANOVA and Kruskal-Wallis

ANOVA Four assumption that are all met H 0: μ 1980 = μ 1990 = μ 2000 vs. H 1 : μ 1980 ≠ μ 1990 ≠μ 2000 PER: F-statistic of 2.06, p-value of.129 PPG: F-statistic of 1.50, p-value of.225 APG: F-statistic of.64, p-value of.53 RPG: F-statistic of 4.06, p-value of.018

Kruskal-Wallis H 0 : T 1980 =T 1990 =T 2000 vs. H 1 : not all T j ’s are equal PER: H-value of 4.89, p-value of.087 PPG: H-value of 3.51, p-value of.172 APG: H-value was.35, p-value of.84 RPG: H-value of 14.14, p-value of.001

Multiple Comparisons Steel-Dwass-Critchlow-Fligner test T u ≠ T v if w* I j ≥ w* α 1980 and 1990: w* ij = and 2000: w* ij = and 2000: w* ij =

Conclusion The prime of an NBA player’s career is not at age 27 The prime for a player has not changed in the last thirty years, except for rebounding