# of people per square kilometer # of assaults................... SCATTERPLOT OF ASSAULTS BY # OF PEOPLE PER SQUARE KILOMETER.

Slides:



Advertisements
Similar presentations
Chapter 9: Simple Regression Continued
Advertisements

Chi Square Your report 2. Intro Describe your trait you selected – What is the dominant and recessive trait – How did you collect the data? – What is.
Eight backpackers were asked their age (in years) and the number of days they backpacked on their last backpacking trip. Is there a linear relationship.
CHI-SQUARE(X2) DISTRIBUTION
Exam Feb 28: sets 1,2 Set 1 due Thurs Memo C-1 due Feb 14 Free tutoring will be available next week Plan A: MW 4-6PM OR Plan B: TT 2-4PM VOTE for Plan.
C 3.7 Use the data in MEAP93.RAW to answer this question
Chapter 14, part D Statistical Significance. IV. Model Assumptions The error term is a normally distributed random variable and The variance of  is constant.
1 Multiple Regression A single numerical response variable, Y. Multiple numerical explanatory variables, X 1, X 2,…, X k.
Correlation Correlation is the relationship between two quantitative variables. Correlation coefficient (r) measures the strength of the linear relationship.
July 1, 2008Lecture 17 - Regression Testing1 Testing Relationships between Variables Statistics Lecture 17.
Correlation and Simple Regression Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.
Hypothesis Testing Steps of a Statistical Significance Test. 1. Assumptions Type of data, form of population, method of sampling, sample size.
Stat 217 – Day 27 Topics in Regression. Last Time – Inference for Regression Ho: no association or  =0 Ha: is an/positive/negative association Minitab.
1 An example. 2 AirlinePercentage on time Complaints Southwest Continental Northwest US Airways United American
The Basics of Regression continued
Business Statistics - QBM117 Interval estimation for the slope and y-intercept Hypothesis tests for regression.
Inferences about the slope of the regression line.
Lecture 5 Correlation and Regression
STA291 Statistical Methods Lecture 27. Inference for Regression.
Formulas: Hypothesis test: We would like to know if there is . The data on six-year graduation rate (%), student-related expenditure per full-time.
Basic Statistics. Basics Of Measurement Sampling Distribution of the Mean: The set of all possible means of samples of a given size taken from a population.
Anthony Greene1 Correlation The Association Between Variables.
Data Analysis (continued). Analyzing the Results of Research Investigations Two basic ways of describing the results Two basic ways of describing the.
© 2008 McGraw-Hill Higher Education The Statistical Imagination Chapter 15: Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.
AP Statistics Chapter 27 Notes “Inference for Regression”
Inference for Regression Chapter 14. Linear Regression We can use least squares regression to estimate the linear relationship between two quantitative.
12.1 WS Solutions. (b) The y-intercept says that if there no time spent at the table, we would predict the average number of calories consumed to be
Regression Lines. Today’s Aim: To learn the method for calculating the most accurate Line of Best Fit for a set of data.
Section 9.2 Hypothesis Testing Proportions P-Value.
PY 603 – Advanced Statistics II TR 12:30-1:45pm 232 Gordon Palmer Hall Jamie DeCoster.
Chapter 20: Testing Hypotheses About Proportions AP Statistics.
Statistics for Business and Economics 8 th Edition Chapter 11 Simple Regression Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Ch.
The Statistical Imagination Chapter 15. Correlation and Regression Part 2: Hypothesis Testing and Aspects of a Relationship.
Political Science 30: Political Inquiry. Linear Regression II: Making Sense of Regression Results Interpreting SPSS regression output Coefficients for.
Environmental Modeling Basic Testing Methods - Statistics III.
Click to edit Master title style Midterm 3 Wednesday, June 10, 1:10pm.
PS 225 Lecture 17 Correlation Line Review. Scatterplot (Scattergram)  X: Independent Variable  Y: Dependent Variable  Plot X,Y Pairs Length (in)Weight.
June 30, 2008Stat Lecture 16 - Regression1 Inference for relationships between variables Statistics Lecture 16.
The Assessment of Improved Water Sources Across the Globe By Philisile Dube.
Chapter 7 Calculation of Pearson Coefficient of Correlation, r and testing its significance.
1 1 Slide The Simple Linear Regression Model n Simple Linear Regression Model y =  0 +  1 x +  n Simple Linear Regression Equation E( y ) =  0 + 
Correlation. u Definition u Formula Positive Correlation r =
Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall 2015 Room 150 Harvill.
Correlation. The statistic: Definition is called Pearsons correlation coefficient.
3.4 Slope and Rate of Change Math, Statistics & Physics 1.
Area Test for Observations Indexed by Time L. B. Green Middle Tennessee State University E. M. Boczko Vanderbilt University.
Two Categorical Variables: The Chi-Square Test
Spearman’s Rho Correlation
Inference for Regression (Chapter 14) A.P. Stats Review Topic #3
AP Statistics Chapter 14 Section 1.
Political Science 30: Political Inquiry
Do Age, BMI, and History of Smoking play a role?
MATH 2311 Section 8.2.
Chapter 12 Inference on the Least-squares Regression Line; ANOVA
Hypothesis Tests for Proportions
Goodness of Fit The sum of squared deviations from the mean of a variable can be decomposed as follows: TSS = ESS + RSS This decomposition can be used.
Hypothesis Test for Independent Groups Two Proportions
Statistical Inference for Managers
P-VALUE.
Hypothesis tests in linear regression
CHAPTER 12 Inference for Proportions
CHAPTER 12 Inference for Proportions
Example on the Concept of Regression . observation
Chi-Squared AP Biology.
Sample Mean Compared to a Given Population Mean
Sample Mean Compared to a Given Population Mean
Graphs and Chi Square.
Adding variables. There is a difference between assessing the statistical significance of a variable acting alone and a variable being added to a model.
Correlation and Simple Linear Regression
Correlation and Simple Linear Regression
Presentation transcript:

# of people per square kilometer # of assaults SCATTERPLOT OF ASSAULTS BY # OF PEOPLE PER SQUARE KILOMETER

Ho: The slope of the regression line is zero, or negative. Ha: The slope of the regression line is positive. STATISTICAL TRANSLATION OF HYPOTHESIS:

# of people per square kilometer # of assaults SCATTERPLOT OF ASSAULTS BY # OF PEOPLE PER SQUARE KILOMETER WITH REGRESSION LINE

Conclusion: we can reject the null hypothesis that the regression line is zero or negative.