Very Short Guide to Stats for SGR Basics of aggregate and statistical data.

Slides:



Advertisements
Similar presentations
Part III: Designing Psychological Research In Part II of the course, we discussed what it means to measure psychological variables, and how to do so.
Advertisements

Basic Statistical Concepts
Introductory Statistics Options, Spring 2008 Stat 100: MWF, 11:00 Science Center C. Stat 100: MWF, 11:00 Science Center C. –General intro to statistical.
Chapter 13 Conducting & Reading Research Baumgartner et al Data Analysis.
PED 471: Height Histogram Spring Introduction to Statistics Giving Meaning to Measurement Chapter 4:
QM Spring 2002 Statistics for Decision Making Descriptive Statistics.
Statistical Analysis SC504/HS927 Spring Term 2008 Week 17 (25th January 2008): Analysing data.
Importing our Web data and Answering Descriptive Questions about Single Variables Psych 437.
1 Basic statistics Week 10 Lecture 1. Thursday, May 20, 2004 ISYS3015 Analytic methods for IS professionals School of IT, University of Sydney 2 Meanings.
1 Statistical Analysis SC504/HS927 Spring Term 2008 Session 1: Week 16: 18 th January Getting to know your data.
Descriptive statistics (Part I)
The Stats Unit.
Quiz 2 Measures of central tendency Measures of variability.
QUANTITATIVE RESEARCH Hypothesizing, counting, and reporting.
Objective To understand measures of central tendency and use them to analyze data.
Southampton Education School Southampton Education School Dissertation Studies Quantitative Data Analysis.
Basic Definitions  Statistics Collect Organize Analyze Summarize Interpret  Information - Data Draw conclusions.
Class Meeting #11 Data Analysis. Types of Statistics Descriptive Statistics used to describe things, frequently groups of people.  Central Tendency 
BIOSTAT - 2 The final averages for the last 200 students who took this course are Are you worried?
Data Handbook Chapter 4 & 5. Data A series of readings that represents a natural population parameter A series of readings that represents a natural population.
Descriptive Statistics
110/10/2015Slide 1 The homework problems on comparing central tendency and variability extend our focus on central tendency and variability to a comparison.
UNDERSTANDING RESEARCH RESULTS: DESCRIPTION AND CORRELATION © 2012 The McGraw-Hill Companies, Inc.
METHODS IN BEHAVIORAL RESEARCH NINTH EDITION PAUL C. COZBY Copyright © 2007 The McGraw-Hill Companies, Inc.
1.1 EXPLORING STATISTICAL QUESTIONS Unit 1 Data Displays and Number Systems.
Welcome to MM207 - Statistics! Unit 2 Seminar Monday 8:00 – 9:00 pm ET Professor: Dan Watson Good Evening Everyone! To resize your pods: Place your mouse.
Univariate Descriptive Research Recall that the objective of univariate descriptive research is to describe a single psychological variable.
DESCRIPTIVE STATISTICS. Nothing new!! You are already using it!!
Central Tendency. Variables have distributions A variable is something that changes or has different values (e.g., anger). A distribution is a collection.
Chapter Eight: Using Statistics to Answer Questions.
Appendix B: Statistical Methods. Statistical Methods: Graphing Data Frequency distribution Histogram Frequency polygon.
Statistical Analysis Quantitative research is first and foremost a logical rather than a mathematical (i.e., statistical) operation Statistics represent.
The field of statistics deals with the collection,
Statistical Analysis of Data. What is a Statistic???? Population Sample Parameter: value that describes a population Statistic: a value that describes.
1 Outline 1. Why do we need statistics? 2. Descriptive statistics 3. Inferential statistics 4. Measurement scales 5. Frequency distributions 6. Z scores.
Descriptive Statistics. Outline of Today’s Discussion 1.Central Tendency 2.Dispersion 3.Graphs 4.Excel Practice: Computing the S.D. 5.SPSS: Existing Files.
Descriptive Statistics Research Writing Aiden Yeh, PhD.
Why do we analyze data?  It is important to analyze data because you need to determine the extent to which the hypothesized relationship does or does.
Measurements Statistics WEEK 6. Lesson Objectives Review Descriptive / Survey Level of measurements Descriptive Statistics.
Why do we analyze data?  To determine the extent to which the hypothesized relationship does or does not exist.  You need to find both the central tendency.
Chapter15 Basic Data Analysis: Descriptive Statistics.
DESCRIPTIVE STATISTICS. Nothing new!! You are already using it!!
Educational Research Descriptive Statistics Chapter th edition Chapter th edition Gay and Airasian.
PSY 325 AID Education Expert/psy325aid.com FOR MORE CLASSES VISIT
QUANTITATIVE RESEARCH Counting, and reporting. Quantitative Research  Numbers-based – Quantitative research refers to the manipulation of numbers to.
Welcome to MM305 Unit 2 Seminar Dr. Bob Statistical Foundations for Quantitative Analysis.
Slide 1 Copyright © 2004 Pearson Education, Inc.  Descriptive Statistics summarize or describe the important characteristics of a known set of population.
AP PSYCHOLOGY: UNIT I Introductory Psychology: Statistical Analysis The use of mathematics to organize, summarize and interpret numerical data.
Lecture 8 Data Analysis: Univariate Analysis and Data Description Research Methods and Statistics 1.
Statistics in Forensics
Statistical Methods Michael J. Watts
Measurements Statistics
Analysis and Empirical Results
Statistical Methods Michael J. Watts
DESCRIPTIVE STATISTICS
Statistical Reasoning in Everyday Life
Statistics Statistics Principles of EngineeringTM
Module 6: Descriptive Statistics
Statistical Reasoning in Everyday Life
Descriptive and Inferential Statistics
STATS DAY First a few review questions.
Understanding Research Results: Description and Correlation
Statistics Statistics Principles of EngineeringTM
Central Tendency.
Statistics Statistics- Inferential Statistics Descriptive Statistics
10.2 Statistics Part 1.
Psychology Statistics
Statistics: The Interpretation of Data
Descriptive Statistics
Univariate Statistics
Presentation transcript:

Very Short Guide to Stats for SGR Basics of aggregate and statistical data

Inferential v. Descriptive Descriptive statistics “describe” the data of a sample or population. They are usually aggregate data Descriptive statistics “describe” the data of a sample or population. They are usually aggregate data Average (Mean) GPA Average (Mean) GPA Standard Deviation of SAT score Standard Deviation of SAT score Inferential statistics “infer” (i.e. conclude) relationships between a sample AND a population, or “infer” past, present or future results of a sample/population based on its data. Inferential statistics “infer” (i.e. conclude) relationships between a sample AND a population, or “infer” past, present or future results of a sample/population based on its data. Regression/correlation analysis of GPA and SAT (relationship between SAT and GPA, and SAT can be used to predict GPA) Regression/correlation analysis of GPA and SAT (relationship between SAT and GPA, and SAT can be used to predict GPA)

Population v. Sample In inferential statistics, you would refer to the number of participants in your survey as N. If it is a sample or part of a whole, it is n (lowercase), and if it is a total population, it is N (uppercase). In inferential statistics, you would refer to the number of participants in your survey as N. If it is a sample or part of a whole, it is n (lowercase), and if it is a total population, it is N (uppercase). Population: N = 4,432 Population: N = 4,432 Sample: n = 100 Sample: n = 100 In descriptive studies and descriptive statistics, it is common to refer to participants as N, subgroups of those participants as n In descriptive studies and descriptive statistics, it is common to refer to participants as N, subgroups of those participants as n Of the total students surveyed (N = 100), only 10% (n = 10) were male. Of the total students surveyed (N = 100), only 10% (n = 10) were male. For the SGR, you would refer to then the participants as N since this is a descriptive study. For the SGR, you would refer to then the participants as N since this is a descriptive study.

Descriptive Stats 101 Central Tendency measures common “middles” Central Tendency measures common “middles” Mean is the arithmetic average of items or values Mean is the arithmetic average of items or values Mode is the most occurring item or value Mode is the most occurring item or value Median is the item or value of which 50% are greater and 50% are less. Median is the item or value of which 50% are greater and 50% are less. Sometimes GPA or time can be used as a measure, but another measure is one of attitudes and beliefs using a Likert-type scale. Sometimes GPA or time can be used as a measure, but another measure is one of attitudes and beliefs using a Likert-type scale. Standard Deviation is a measure of the spread of items or values in a series. Understanding the variation can help you see how close a particular item or value is to other numbers. Standard Deviation is a measure of the spread of items or values in a series. Understanding the variation can help you see how close a particular item or value is to other numbers. Distribution (Histogram) is a visual representation of the number of a particular result in an array of numbers. Distribution (Histogram) is a visual representation of the number of a particular result in an array of numbers. In this series (number of hours I played WoW over break): 8, 0, 0, 3, 2, 10, 0 Mean = 3.29, Mode = 0, Median = 2, SD = 4.11 Mean = 3.29, Mode = 0, Median = 2, SD = 4.11 In this series (number of hours I worked this week): 8, 8, 8, 8, 6, 6, 5 Mean = 7, Mode = 8, Median = 8, SD = 1.29 Mean = 7, Mode = 8, Median = 8, SD = 1.29

Using Excel to do your stats Mean { =average(range) } Mean { =average(range) } You can compute mode { =mode(range) } or median {=median(range) }, but they might not be as useful in this project. You can compute mode { =mode(range) } or median {=median(range) }, but they might not be as useful in this project. Standard Deviation { =stdev(range) } Standard Deviation { =stdev(range) } You can also count the number of instances of a value including instances of text: { =countif(range,”value”) } You can also count the number of instances of a value including instances of text: { =countif(range,”value”) } The following example would count every instance of “male” in the range: The following example would count every instance of “male” in the range: =countif(A2:A7,”male”) =countif(A2:A7,”male”) You can create frequency distribution histograms by using Tools -> Data Analysis, then Historgram. Histograms count the number of instances of a result in a given array. You can create frequency distribution histograms by using Tools -> Data Analysis, then Historgram. Histograms count the number of instances of a result in a given array. You can also find these commands by using Insert -> Function. There are also far more complex inferential statistics available in Excel You can also find these commands by using Insert -> Function. There are also far more complex inferential statistics available in Excel You can do a complete Descriptive Stats Summary by selecting Tools > Data Analysis (If you don’t see a Data Analysis, then (Excel 2003) Tools > Add-ins > Analysis ToolPak; (Excel 2007) Excel Options > Add-ins > Manage Add-ins > Analysis ToolPak You can do a complete Descriptive Stats Summary by selecting Tools > Data Analysis (If you don’t see a Data Analysis, then (Excel 2003) Tools > Add-ins > Analysis ToolPak; (Excel 2007) Excel Options > Add-ins > Manage Add-ins > Analysis ToolPak

Writing Stats in APA Standard Deviation = SD Standard Deviation = SD Mean = M Mean = M Descriptive statistics are often written in parentheses after an item that the statistic refers to, and symbols and numbers should be separated by a space Descriptive statistics are often written in parentheses after an item that the statistic refers to, and symbols and numbers should be separated by a space In a survey of DU students, participants (N = 100) responded that money was more important (M = 4.2, SD =.9) than experience (M = 3.5, SD =.76) in selecting a summer job. In a survey of DU students, participants (N = 100) responded that money was more important (M = 4.2, SD =.9) than experience (M = 3.5, SD =.76) in selecting a summer job. In a survey of computer game addicts, females (n = 15) were more likely to be depressed during withdrawal (M = 5.2, SD =.45) than males were (n = 78, M = 3.2, SD =.98) In a survey of computer game addicts, females (n = 15) were more likely to be depressed during withdrawal (M = 5.2, SD =.45) than males were (n = 78, M = 3.2, SD =.98) If unsure about how to write a statistic in your SGR, you can consult the APA Manual (in the library), ask me, or visit If unsure about how to write a statistic in your SGR, you can consult the APA Manual (in the library), ask me, or visit

Charts and Graphs Pie graphs – good for showing distributions of a total population (you will have to compute aggregates first) Pie graphs – good for showing distributions of a total population (you will have to compute aggregates first) Line graphs – good for showing time-based, linear progression Line graphs – good for showing time-based, linear progression Column/Bar graphs – good for showing distribution of individual responses (you will have to create aggregates first) Column/Bar graphs – good for showing distribution of individual responses (you will have to create aggregates first) Y-Axis (vertical) for variables, X-Axis (horizontal) for participants. Y-Axis (vertical) for variables, X-Axis (horizontal) for participants.

Exercise Perform countif function on gender and major (you will have to create an area for your results that lists the gender/major options). This is just practice doing these two functions and you don’t have to relate them to the next steps. Perform countif function on gender and major (you will have to create an area for your results that lists the gender/major options). This is just practice doing these two functions and you don’t have to relate them to the next steps. Pick two or more variables to compare and write a paragraph in APA style using appropriate symbols (M, SD, N, n ) about the data. Pick two or more variables to compare and write a paragraph in APA style using appropriate symbols (M, SD, N, n ) about the data. Create a graph of some variable or detail of the data, labeling the legend and series items. Create a graph of some variable or detail of the data, labeling the legend and series items.