Does Age Effect Grade Point Average? By Amanda Darrow and Dennis de Melo.

Slides:



Advertisements
Similar presentations
Covariance and Correlation: Estimator/Sample Statistic: Population Parameter: Covariance and correlation measure linear association between two variables,
Advertisements

CAFFEINE CONSUMPTION VS. HOURS OF SLEEP Amie Radtke, Julie Luckart, Drew Hanson, Sofiya Mykhalska, Melissa Young, Erin Brown.
Agresti/Franklin Statistics, 1 of 63  Section 2.4 How Can We Describe the Spread of Quantitative Data?
Descriptive Statistics: Numerical Measures
Descriptive Statistics A.A. Elimam College of Business San Francisco State University.
1 1 Slide © 2003 South-Western/Thomson Learning TM Slides Prepared by JOHN S. LOUCKS St. Edward’s University.
Five-Number Summary 1 Smallest Value 2 First Quartile 3 Median 4
A.P. Statistics: Semester 1 Review
Hypothesis Testing For a Single Population Mean. Example: Grade inflation? Population of 5 million college students Is the average GPA 2.7? Sample of.
Alan Mangus Math April 15,  Purpose of the study (the research question): Can the age of adult male humans be used as a reliable predictor.
Measures of Central Tendency
Group 3: Joscie Barrow, Nicole Devey, Megan Hanson, Shealyn Kwan-Smith, and Gregory Morrison.
Data Handling GCSE coursework. Hypothesis Collection of Data Data Handling GCSE coursework Hypothesis.
Chapter 3 - Part B Descriptive Statistics: Numerical Methods
1 1 Slide © 2001 South-Western /Thomson Learning  Anderson  Sweeney  Williams Anderson  Sweeney  Williams  Slides Prepared by JOHN LOUCKS  CONTEMPORARYBUSINESSSTATISTICS.
1 1 Slide © 2009 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.
Data Analysis: Part 3 Lesson 7.1. Data Analysis: Part 3 MM2D1. Using sample data, students will make informal inferences about population means and standard.
Chapter 3 Descriptive Statistics: Numerical Methods Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin.
Group participation McKie Delahunty- created slides 1,4,5,6,7,8,11,12 & compiled all for powerpoint Jenica Hansen- created slides 2,3 Semhar Moges- created.
1 1 Slide Slides Prepared by JOHN S. LOUCKS St. Edward’s University © 2002 South-Western/Thomson Learning.
McGraw-Hill/Irwin Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. Chapter 3 Descriptive Statistics: Numerical Methods.
Measures of Position. ● The standard deviation is a measure of dispersion that uses the same dimensions as the data (remember the empirical rule) ● The.
Probability & Statistics Sections 2.3, 2.4. A. The mean is very low. B. The data values are all very close in value. C. The data values must all be the.
Does time spent on Facebook affect your grades? Study results presented by: Mary Vietti : Power Point Creator Justin Price : Editor & Conclusion Jacob.
Chapter 8 Making Sense of Data in Six Sigma and Lean
1 1 Slide STATISTICS FOR BUSINESS AND ECONOMICS Seventh Edition AndersonSweeneyWilliams Slides Prepared by John Loucks © 1999 ITP/South-Western College.
Section 6.8 Compare Statistics from Samples. Vocabulary Quartile: The median of an ordered data set Upper Quartile: The median of the upper half of an.
Numerical Measures of Variability
Chelsie Guild, Taylor Larsen, Mary Magee, David Smith, Curtis Wilcox TERM PROJECT- VISUAL PRESENTATION.
Political Science 30: Political Inquiry. Linear Regression II: Making Sense of Regression Results Interpreting SPSS regression output Coefficients for.
Engineering Statistics KANCHALA SUDTACHAT. Statistics  Deals with  Collection  Presentation  Analysis and use of data to make decision  Solve problems.
Summary Statistics and Mean Absolute Deviation MM1D3a. Compare summary statistics (mean, median, quartiles, and interquartile range) from one sample data.
Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 3 Section 4 – Slide 1 of 23 Chapter 3 Section 4 Measures of Position.
Group 4 Members and Participants Amelia Corey, Angie Coates, Cynthia Bradwisch, Aaron Grow, and Daniel Champion.
What’s with all those numbers?.  What are Statistics?
Statistics Group 1 Elisabeth Brino Jamie Derbidge Slade Litten Kristen Kidder Jamie.
STATISTICS 1040 TERM PROJECT SPRING THE QUESTION Is a student’s Grade Point Average (GPA) correlated with their age?
Do Your Parents Affect Your Future? A survey at Deering High School tells you why. By Sarah Muzzy.
For adult men, is the amount of money spent per week on fast food related to body weight? By: Chad Vigil, Jeannette Watson, Jason Williams, Amanda Webster,
Confidence Intervals for a Population Mean, Standard Deviation Unknown.
Group members: Miles, Haylee, David, and Nai. SYSTOLIC BLOOD PRESSURE:WEEKLY HOURS WORKED:
Does Regular Exercise Improve GPA? By Kristin Miller, Patrick Ruhr, and Amna Sultan Introduction Through conversations with friends and other students,
Purpose Data Collection Results Conclusion Sources We are evaluating to see if there is a significant linear correlation between the shoe size and height.
Is there a correlation between the number of hours a student works and the number of credit hours they are enrolled in? Data Compiled and presented by:
5-Minute Check on Activity 7-9 Click the mouse button or press the Space Bar to display the answers. 1.What population parameter is a measure of spread?
Term Project Math 1040-SU13-Intro to Stats SLCC McGrade-Group 4.
SYSTOLIC BLOOD PRESSURE VS. WEEKLY HOURS WORKED BY NURSES Group members: Miles, Haylee, David, and Nai.
Math 1040 Term Project Group 2 Stacey Perko Shanda Miller Stephanie Baker Ben Mansell Heidi Kaibetoney.
Statistics -Descriptive statistics 2013/09/30. Descriptive statistics Numerical measures of location, dispersion, shape, and association are also used.
Lesson Measures of Position. Objectives Determine and interpret z-scores Determine and interpret percentiles Determine and interpret quartiles Check.
FOR TEEN AND YOUNG ADULT MALES (13 TO 29) IS AGE RELATED TO THE NUMBER OF HOURS SPENT PLAYING VIDEO/COMPUTER GAMES? By Amanda Webster, Jennifer Burgoyne,
Chapter 7 Estimation. Chapter 7 ESTIMATION What if it is impossible or impractical to use a large sample? Apply the Student ’ s t distribution.
Mean and Standard Deviation
Line Plots & Box-and-Whiskers Plots
8.4: Calculating and Interpreting Standard Deviation
Math 21 Midterm Review Part 1: Chapters 1-4.
Averages and Variation
Jeopardy Final Jeopardy Chapter 1 Chapter 2 Chapter 3 Chapter 4
Unit 7: Statistics Key Terms
Describing Distributions Numerically
Chapter 3 Section 4 Measures of Position.
Representation of Data
Jeopardy Statistical Measures Click to begin..
Does time spent on Facebook affect your grades?
Advanced Placement Statistics Ch 1.2: Describing Distributions
Click the mouse button or press the Space Bar to display the answers.
Statistics Vocabulary Continued
SnapChat Mini-Project
Statistics Vocabulary Continued
Presentation transcript:

Does Age Effect Grade Point Average? By Amanda Darrow and Dennis de Melo

Does age determine a higher or lower grade point average? By Using a sample of 50 from the population of Salt Lake Community College Students, we will determine if there is in fact a correlation between age and G.P.A.

Collecting the Data A questionnaire was handed out to 50 Salt Lake Community College Students. The questionnaire asked two questions: The participants age The participants grade point average

Charts: Averages and Samples AgeAverage G.P.A Age (18-42) Number of Samples Grade Point AverageNumber of Samples

Age Statistics Mean: 23.5 Range: 42-18= 24 Mode= 19 Outliers: No Outliers

Age 5-Number Summary L=18 Q1= 20IQR: 29-20= 9 µ= 23.5 Lower Fence:0-1.5(9) = 6.5 Q3= 29Upper Fence: (9) = 42.5 H= 42

Age Standard Deviation = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= ∑(x) = 50 µx= 50/12= 4.2 ∑(X1-µ) = /12= 9.31 √9.31 = 3.05

G.P.A. Statistics Mean: 3.1 Range: = 1.5 Mode= 2.6, 2.7, 2.8, 3.1, 3.3, 3.7 and 3.9 Outliers: No Outliers

G.P.A. 5-Number Summary L=2.5 Q1= 2.75IQR: = 0.8 µ= 3.1LF: (0.8) = 1.55 Q3= 3.55UF: (0.8) = 4.75 H= 4.0

G.P.A Standard Deviation = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= = = ²= 0.36 ∑(x) = 39.6 ∑(X1-µ) = 2.12 µx=9.6/12= /12= √0.177= 0.421

Linear Correlation Coefficient AgeAverage G.P.A Correlation: N=19-1 = 18 Table II: 18 = Since the final coefficient is smaller than the correlation we have a linear relation