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The variables in the data set are as follows: Brand: The brand name of the cereal More information INTERPRETING THE ONE-WAY ANALYSIS OF VARIANCE (ANOVA) As with other parametric statistics, we begin the one-way ANOVA with a test of the underlying assumptions. Note: You could also select the single dynamic seed radio button, if you like, to set the seed. Choose the type of histogram (frequency or relative frequency). Our first assumption is the assumption of More information Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables Discrete vs. Section 2.1 Drawing Bar Graphs and Pie Charts Frequency or Relative Frequency Distributions from Raw Data 2. Section 2.2 Drawing Histograms, Stem-and-Leaf Plots, and Dot Plots Histograms 2. You have the option of choosing a lower class limit for the first class by entering a value in the cell marked Start bins at:. 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Essentials of Business, 2nd edition, Mc Graw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Select the column that contains the data for Sample 2. If you choose the confidence interval radio button, enter the level of confidence. Section 11.3 Inference about Two Population Proportions Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight, Goodness-of-fit, then highlight Chi-Square test. Select the column that contains the observed counts and select the column that contains the expected counts. Section 12.2 Tests for Independence and Homogeneity of Proportions 1. Either enter the raw data in separate columns for each sample or treatment, or enter the value of the variable in a single column with indicator variables for each sample or treatment in a second column. In column var1, enter the block of the response variable; in column var2, enter the treatment of the response variable; and in column var3, enter the value of the response variable. 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Section 14.2 Confidence and Predication Intervals Follow the steps given in Section 14.1 for testing the significance of the least-squares regression model. To find the lower and upper limit of the standard deviation, take the square root of the L. Note that the differences are computed Sample 1 Sample 2. If you choose the confidence interval radio button, enter the level of confidence. Section 11.2 Inference for Two Means: Independent Samples Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight T Statistics, select Two sample, and then choose either with data or with 3. If the raw data are in separate columns select Compare selected columns and then click the columns you wish to compare. Repeat the steps for conducting a one-way analysis of variance. Select the column containing the blocks in the pull-down menu Row factor in:. Then choose to save the residuals and then draw a QQ-plot and boxplot of the residuals. 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To construct a confidence interval for the slope, click the Confidence Intervals radio button and choose a level of confidence. Note: If you wish to assess the normality of the residuals, click Next instead of Calculate in Step 4. Select Stat, highlight Proportions, select One sample, and then choose either with data or with 3. Enter the value of the proportion stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. If you chose with data, select the column that has the observations, then click Next. Select Stat, highlight Variance, select One sample, and then choose either with data or with 3. Enter the value of the variance stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Section 11.1 Inference of Two Means: Dependent Samples Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight T Statistics, select Paired. Select the column that contains the data for Sample 1. Section 13.4 Two-Way Analysis of Variance Obtaining Two-Way ANOVA 1. Select the column containing the column factor in the pull-down menu Column factor in:. Section 14.1 Testing the Significance of the Least-Squares Regression Model 2. Select Stat, highlight T Statistics, select One sample, and then choose either with data or with 3. Enter the value of the mean stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Section 10.4 Hypothesis Tests for a Population Standard Deviation 2. Select the column containing the row factor in the pull-down menu Row factor in:. Select the Display means table box to use for Tukey s test. Interaction Plots In the same screen where you checked Display means table, also check Plot interactions. Select the column containing the values of response variable for the pull-down menu Responses in:. 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Enter labels for the x- and y-axes, and enter a title for the graph. continuous random variables Examples of continuous distributions o Uniform o Exponential o Normal Recall: A random More information EXCEL Tutorial: How to use EXCEL for Graphs and Calculations. Select Stat, highlight Tables, and select Frequency. Click on the variable you wish to summarize and click Calculate. Enter the summarized data table into the spreadsheet. Enter the summarized data table into the spreadsheet. You have the option of choosing a class width by entering a value in the cell marked Binwidth:. Excel is powerful tool and can make your life easier if you are proficient in using it. Name the variable and frequency (or relative frequency) column. Select Graphics, highlight Bar Plot, then highlight with 3. Enter labels for the x- and y-axes, and enter a title for the graph. Name the variable and frequency (or relative frequency) column. Select Graphics, highlight Pie Chart, then highlight with 3. Select the Categories in: column and Counts in: column. Select the Categories in: column and Counts in: column. More information How To Run Statistical Tests in Excel Microsoft Excel is your best tool for storing and manipulating data, calculating basic descriptive statistics such as means and standard deviations, and conducting More information Chapter 340 Principal Components Regression Introduction is a technique for analyzing multiple regression data that suffer from multicollinearity. It consists of a sequence More information An introduction to IBM SPSS Statistics Contents 1 Introduction... One-Way More information Elementary Statistics Sample Exam #3 Instructions. Note 11B: Normal Graphs More information Describing Data: Categorical and Quantitative Variables Population The Big Picture Sampling Statistical Inference Sample Exploratory Data Analysis Descriptive Statistics In order to make sense of data, More information Study Guide for the Final Exam When studying, remember that the computational portion of the exam will only involve new material (covered after the second midterm), that material from Exam 1 will make More information Chapter 3 RANDOM VARIATE GENERATION In order to do a Monte Carlo simulation either by hand or by computer, techniques must be developed for generating values of random variables having known distributions. Enter labels for the x- and y-axes, and enter a title for the graph. Section 3.5 The Five-Number Summary and Boxplots Boxplots 2. These add-ins tools work on top of Excel, extending its power and abilities More information SAS Software to Fit the Generalized Linear Model Gordon Johnston, SAS Institute Inc., Cary, NC Abstract In recent years, the class of generalized linear models has gained popularity as a statistical modeling More information SPSS Introduction Yi Li Note: The report is based on the websites below information A Correlation of to the South Carolina Data Analysis and Probability Standards INTRODUCTION This document demonstrates how Stats in Your World 2012 meets the indicators of the South Carolina Academic Standards More information Statistics Chapter 2 Frequency Tables A frequency table organizes quantitative data. mark@More information Probability and Statistics Vocabulary List (Definitions for Middle School Teachers) B Bar graph a diagram representing the frequency distribution for nominal or discrete data. When pressed, a CHOOSE More information UNIVERSITY OF TORONTO SCARBOROUGH Department of Computer and Mathematical Sciences Midterm Test March 2014 STAB22H3 Statistics I Duration: 1 hour and 45 minutes Last Name: First Name: Student number: Aids More information MINITAB ASSISTANT WHITE PAPER This paper explains the research conducted by Minitab statisticians to develop the methods and data checks used in the Assistant in Minitab 17 Statistical Software. More information CHAPTER 11 Calculator Notes for the Note 11A: Entering e In any application, press u to display the value e. after you press u to display the value of e without an exponent. Section 3.4 Measures of Position and Outliers The same steps followed to obtain measures of central tendency from raw data can be used to obtain the measures of dispersion. Click on the variable whose boxplot you want to draw and click Next. Enter labels for the x- axis and enter a title for the graph. Section 4.1 Scatter Diagrams and Correlation Scatter Diagrams 2. For example, to simulate rolling a single die, enter 1 and 6, respectively. Select either the dynamic seed, or select the fixed seed and enter a value of the seed. In the Group by: cell, also select the column the simulated data is located in. First row keys like \ R (67/276 are used to obtain More information DESCRIPTIVE STATISTICS The purpose of statistics is to condense raw data to make it easier to answer specific questions; test hypotheses. INFERENTIAL STATISTICS Descriptive To organize, More information STATISTICAL ANALYSIS WITH EXCEL COURSE OUTLINE Perhaps Microsoft has taken pains to hide some of the most powerful tools in Excel. Test Score Number of Students More information Normality Testing in Excel By Mark Harmon Copyright 2011 Mark Harmon No part of this publication may be reproduced or distributed without the express permission of the author. 14 5 Generating descriptive More information The STAT menu Trend Lines Practice predicting the future using trend lines The STAT menu The Statistics menu is accessed from the ORANGE shifted function of the 5 key by pressing Ù. SCOTT STREET, IV DEPARTMENT OF STATISTICAL SCIENCES & OPERATIONS RESEARCH VIRGINIA COMMONWEALTH UNIVERSITY Table More information Appendix 2.1 Tabular and Graphical Methods Using Excel 1 Appendix 2.1 Tabular and Graphical Methods Using Excel The instructions in this section begin by describing the entry of data into an Excel spreadsheet. Select Stat, highlight Summary Stats, and select Columns. Deselect any statistics you do not wish to compute. Section 3.2 Measures of Dispersion The same steps followed to obtain measures of central tendency from raw data can be used to obtain the measures of dispersion. Choose the explanatory variable for the X variable and the response variable for the Y variable. Select Stat, highlight Summary Stats, and select Correlation. Click on the variables whose correlation you wish to determine. The coefficient of determination is given as part of the output (R-sq). Select Stat, highlight Regression, and select Simple Linear. Choose the explanatory variable for the X variable and the response variable for the Y variable. Title each column (including the first column indicating the row variable). Select Stats, highlight Tables, select Contingency, then highlight with 3. For example, if we want to simulate rolling a die 100 times, enter 100. Enter the smallest and largest integer in the Minimum: and Maximum: cell, respectively. Select Stats, highlight Tables, select Contingency, then highlight with data. To get counts, select Stat, highlight Summary Stats, then select Columns. Select the column the simulated data is located in. (In an assignment you may be told what class boundaries to More information Correlation and Regression Scatterplots Correlation Explanatory and response variables Simple linear regression General Principles of Data Analysis First plot the data, then add numerical summaries Look More information Figure 9-6 Example: Boats and Manatees Slide 1 Given the sample data in Table 9-1, find the value of the linear correlation coefficient r, then refer to Table A-6 to determine whether there is a significant More information 2 Describing, Exploring, and Comparing Data This chapter introduces the graphical plotting and summary statistics capabilities of the TI- 83 Plus. A chi square goodness of fit test is considered to More information STATS8: Introduction to Biostatistics Data Exploration Babak Shahbaba Department of Statistics, UCI Introduction After clearly defining the scientific problem, selecting a set of representative members More information USING A TI-83 OR TI-84 SERIES GRAPHING CALCULATOR IN AN INTRODUCTORY STATISTICS CLASS W. Select Stat, highlight Regression, and select Simple Linear. Choose the explanatory variable for the X variable and the response variable for the Y variable. Section 4.3 Diagnostics on the Least-Squares Regression Line Coefficient of Determination Follow the same steps used to obtain the least-squares regression line. For the data in Table 8, enter the counts for each level of education. For example, the data in Table 8 has four column variables ( Did Not Finish High School, and so on) and the row label is employment status. Select Data, highlight Simulate Data, then highlight Discrete Uniform. Enter the numbers of random numbers you would like generated in the Rows: cell. Select Stats, highlight Calculators, select Binomial. In the pull-down menu, decide if you wish to compute P(X x). Select Stats, highlight Calculators, select Normal. More information Drawing a histogram using Excel STEP 1: Examine the data to decide how many class intervals you need and what the class boundaries should be. Each subsequent column would be the counts of each category of the column variable. Section 6.2 The Binomial Probability Distribution 1. Enter the number of trials, n, and probability of success, p. If given the area to the left, in the pull-down menu choose the Section 7.3 Applications of the Normal Distribution Finding Areas under the Standard Normal Curve 1. Working with Data Entering and Formatting Data Before entering data More information AP Statistics: Syllabus 1 Scoring Components SC1 The course provides instruction in exploring data. 5 SC3 The course provides instruction in experimentation. For example, for the data in Table 8, the first column would be employment status. Select Stats, highlight Calculators, select Normal. In the pull-down menu, decide if you are given area to the left of the unknown z-score, or the area to the right. In the pull-down menu, decide if you wish to compute P(X x). Refer to the Excel help files for more information. Enter 0 for the mean and 1 for the Standard Deviation. More information Mgt 540 Research Methods Data Analysis 1 Additional sources Compilation of sources: information Chapter 3 Student Lecture Notes 3- Chapter 3 Introduction to Linear Regression and Correlation Analsis Fall 2006 Fundamentals of Business Statistics Chapter Goals To understand the methods for displaing More information NEW YORK CITY COLLEGE OF TECHNOLOGY The City University of New York DEPARTMENT: Mathematics COURSE: MAT 1272/ MA 272 TITLE: DESCRIPTION: TEXT: Statistics An introduction to statistical methods and statistical More information Excel Tutorial Below is a very brief tutorial on the basic capabilities of Excel. Select Stats, highlight Calculators, select Normal. Type More information Step 1: Regression step-by-step using Microsoft Excel Notes prepared by Pamela Peterson Drake, James Madison University Type the data into the spreadsheet The example used throughout this How to is a regression More information PELLISSIPPI STATE COMMUNITY COLLEGE MASTER SYLLABUS INTRODUCTION TO STATISTICS MATH 2050 Class Hours: 2.0 Credit Hours: 3.0 Laboratory Hours: 2.0 Date Revised: Fall 2013 Catalog Course Description: Descriptive More information Table of Contents Introduction to Minitab...2 Example 1 One-Way ANOVA...3 Determining Sample Size in One-way ANOVA...8 Example 2 Two-factor Factorial Design...9 Example 3: Randomized Complete Block Design...14 More information 1 Simple Linear Regression, Scatterplots, and Bivariate Correlation This section covers procedures for testing the association between two continuous variables using the SPSS Regression and Correlate analyses. If given the area to the left, in the pulldown menu choose the option. Set up the spreadsheet page (Sheet 1) so that anyone who reads it will understand the page (Figure 1). In the pull-down menu, decide if you are given area to the left of the unknown score, or the area to the right. Rummel BBA Seminar 1 / 54 Excel Calculations of Descriptive Statistics Single Variable Graphs Relationships More information Entering and Formatting Data Using Microsoft Excel to Plot and Analyze Kinetic Data Open Excel. This chapter More information Examples 319 List of Examples Di Maggio and Mantle. Using the textbook readings and other resources listed on the web More information INTRODUCTORY STATISTICS FIFTH EDITION Thomas H. Wonnacott University of Western Ontario WILEY JOHN WILEY & SONS New York Chichester Brisbane Toronto Singapore More information : Table of Contents... Rummel Emory University Goizueta Business School BBA Seminar Jeffrey L. Describing, Exploring, and Comparing Data There are many tools used in Statistics to visualize, summarize, and describe data. 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The Math Book of Problems Series is a database of math problems for the following courses: Pre-algebra Algebra Pre-calculus Calculus Statistics More information Mathematics Probability and Statistics Curriculum Guide Revised 2010 This page is intentionally left blank. Descriptive statistics are distinguished from inferential statistics (or inductive statistics), More information Microsoft Excel Qi Wei Excel (Microsoft Office Excel) is a spreadsheet application written and distributed by Microsoft for Microsoft Windows and Mac OS X. If your computer does not have that tool More information Summarizing and Displaying Categorical Data Categorical data can be summarized in a frequency distribution which counts the number of cases, or frequency, that fall into each category, or a relative frequency More information Geo Gebra Statistics and Probability Project Maths Development Team 2013 1 of 24 Index Activity Topic Page 1 Introduction Geo Gebra Statistics 3 2 To calculate the Sum, Mean, Count, More information Mathematics Fairfield Public Schools AP Statistics AP Statistics BOE Approved 04/08/2014 1 AP STATISTICS Critical Areas of Focus AP Statistics is a rigorous course that offers advanced students an opportunity More information 1) Write the following as an algebraic expression using x as the variable: Triple a number subtracted from the number A. 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Specifically, More information Data used in this guide: ( Organize and Display One Quantitative Variable (Descriptive Statistics, Boxplot & Histogram) 1. Brief Version of the Case Study 15.1 Problem Formulation 15.2 Selection of Factors 15.3 Obtaining Random Samples of Paper Towels 15.4 How will the Absorbency be measured? A common situation is for a data set to be represented as a matrix. 1-4) Definitions Population: The complete set of numerical information on a particular quantity in which an investigator is interested. If you chose with data, select the column that has the observations, choose which outcome represents a success, then click Next. The following will give a description of each of them. x - 3x 2) Write the following as an algebraic expression More information 1 One-Way ANOVA using SPSS 11.0 This section covers steps for testing the difference between three or more group means using the SPSS ANOVA procedures found in the Compare Means analyses. 5 Summary More information Exploratory Data Analysis Exploratory Data Analysis involves both graphical displays of data and numerical summaries of data. Published by More information Summary of Formulas and Concepts Descriptive Statistics (Ch. Select Stat, highlight Proportions, select One sample, and then choose either with data or with 3. If you choose the confidence interval radio button, enter the level of confidence. If the data is not in a contingency table, enter each variable in a column and name the column variable. Select Stats, highlight Tables, select Contingency, then highlight with data or with 3. A and B This represents the probability that both events A and B occur. Inferences for Regression Topics covered in this chapter: Simple Linear Regression Simple Linear Regression Example 23.1: Crying and IQ The Problem: Infants who cry easily may be more easily More information SPSS Basics Tutorial 1: SPSS Windows There are six different windows that can be opened when using SPSS. Section 9.1 Confidence Intervals for a Proportion 2. If necessary, enter the raw data into the first two columns of the spreadsheet. If you chose with data, select each column that has the observations, then click Next. If you choose the hypothesis test radio button, enter the value of the ratio of the variance stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Title each column (including the first column indicating the row variable). For example, the data in Table 8 has four column variables ( Did Not Finish High School, and so on) and the row label is employment status. More information Business Course Text Bowerman, Bruce L., Richard T. To run the Explore procedure, More information Course Text Business Statistics Lind, Douglas A., Marchal, William A. The first part concerns commands in JMP, the second part is for analysis More information Glossary Brase: Understandable Statistics, 10e A B This is the notation used to represent the conditional probability of A given B. If you choose the confidence interval radio button, enter the level of confidence. Section 11.4 Inference about Two Population Standard Deviations 1. Select Stat, highlight Variance, select Two sample, and then choose either with data or with 3. For the data in Table 8, enter the counts for each level of education. Click Next Bowerman, O'Connell, Aitken Schermer, & Adcock, Business Statistics in Practice, Canadian edition Online Learning Centre Technology Step-by-Step - Excel Microsoft Excel is a spreadsheet software application More information MTH 140 Statistics Videos Chapter 1 Picturing Distributions with Graphs Individuals and Variables Categorical Variables: Pie Charts and Bar Graphs Categorical Variables: Pie Charts and Bar Graphs Quantitative More information Individuals: The objects that are described by a set of data. (Also referred to as Cases or Records) Variables: The characteristics recorded about each individual. Click on variable(s) then press to move to into Variable(s): list More information SPSS Explore procedure One useful function in SPSS is the Explore procedure, which will produce histograms, boxplots, stem-and-leaf plots and extensive descriptive statistics. Basic Statistics for Business and Economics, 7th edition, Mc Graw-Hill/Irwin, 2010, ISBN: 9780077384470 [This More information 1 Commands in JMP and Statcrunch Below are a set of commands in JMP and Statcrunch which facilitate a basic statistical analysis. If you chose with data, select the column that has the observations, then click Next. If you chose with data, select the column that has the observations, choose which outcome represents a success for each sample, then click Next. If you choose the hypothesis test radio button, enter the value of the proportion stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Each subsequent column would be the counts of each category of the column variable. Select Stat, highlight Regression, and select Multiple Linear. Choose the response variable for the Y variable, the explanatory variables for the X variables, and any interactions (optional). Required Computing More information SPSS Tests for Versions 9 to 13 Chapter 2 Descriptive Statistic (including median) Choose Analyze Descriptive statistics Frequencies... Select Stat, highlight T Statistics, select One sample, and then choose either with data or with 3. Note that the differences are computed Sample 1 Sample 2. If you have raw data, enter them into the spreadsheet. Select Stat, highlight Proportions, select Two sample, and then choose either with data or with 3. If the data is already in a contingency table, enter it into the spreadsheet. For example, for the data in Table 8, the first column would be employment status. Enter the explanatory variables and response variable into the spreadsheet. Select Stat, highlight Summary Stats, and select Correlation. Click on the variables whose correlation you wish to determine. Determining the Multiple Regression Equation and Residual Plots 2. Essentials of Business, 2nd edition, Mc Graw-Hill/Irwin, 2008, ISBN: 978-0-07-331988-9. Select the column that contains the data for Sample 2. If you choose the confidence interval radio button, enter the level of confidence. Section 11.3 Inference about Two Population Proportions Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight, Goodness-of-fit, then highlight Chi-Square test. Select the column that contains the observed counts and select the column that contains the expected counts. Section 12.2 Tests for Independence and Homogeneity of Proportions 1. Either enter the raw data in separate columns for each sample or treatment, or enter the value of the variable in a single column with indicator variables for each sample or treatment in a second column. In column var1, enter the block of the response variable; in column var2, enter the treatment of the response variable; and in column var3, enter the value of the response variable. At Step 4, click Next and then select Plot the fitted line and check the confidence and prediction interval boxes. Section 14.2 Multiple Regression Correlation Matrix 1. If necessary, enter the raw data into the first two columns of the spreadsheet. Select the column that contains the data for Sample 1. If you choose the hypothesis test radio button, enter the value of the mean stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. If the raw data are in a single column, select Compare values in a single column and then choose the column that contains the value of the variables and the column that indicates the treatment (factor) or sample. In Step 3, check the box Tukey HSD with confidence level:. Section 13.3 The Randomized Complete Block Design 1. Select the column containing the treatment in the pull-down menu Column factor in:. Section 14.2 Confidence and Predication Intervals Follow the steps given in Section 14.1 for testing the significance of the least-squares regression model. To find the lower and upper limit of the standard deviation, take the square root of the L. Note that the differences are computed Sample 1 Sample 2. If you choose the confidence interval radio button, enter the level of confidence. Section 11.2 Inference for Two Means: Independent Samples Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight T Statistics, select Two sample, and then choose either with data or with 3. If the raw data are in separate columns select Compare selected columns and then click the columns you wish to compare. Repeat the steps for conducting a one-way analysis of variance. Select the column containing the blocks in the pull-down menu Row factor in:. Then choose to save the residuals and then draw a QQ-plot and boxplot of the residuals. If you chose with data, select the column that has the observations, choose which outcome represents a success, then click Next. If you chose with data, select the column that has the observations, then click Next. If necessary, enter the raw data into the first two columns of the spreadsheet. Select the column that contains the data for Sample 2. If you choose the hypothesis test radio button, enter the value of the mean stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Select the column containing the values of response variable for the pull-down menu Responses in:. In column var1, enter the level of factor A; in column var2, enter the level of factor B; and in column var3, enter the value of the response variable. Select Stat, highlight Regression, and select Simple Linear. Choose the explanatory variable for the X variable and the response variable for the Y variable. To construct a confidence interval for the slope, click the Confidence Intervals radio button and choose a level of confidence. Note: If you wish to assess the normality of the residuals, click Next instead of Calculate in Step 4. Select Stat, highlight Proportions, select One sample, and then choose either with data or with 3. Enter the value of the proportion stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. If you chose with data, select the column that has the observations, then click Next. Select Stat, highlight Variance, select One sample, and then choose either with data or with 3. Enter the value of the variance stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Section 11.1 Inference of Two Means: Dependent Samples Hypothesis Tests or Confidence Intervals 1. Select Stat, highlight T Statistics, select Paired. Select the column that contains the data for Sample 1. Section 13.4 Two-Way Analysis of Variance Obtaining Two-Way ANOVA 1. Select the column containing the column factor in the pull-down menu Column factor in:. Section 14.1 Testing the Significance of the Least-Squares Regression Model 2. Select Stat, highlight T Statistics, select One sample, and then choose either with data or with 3. Enter the value of the mean stated in the null hypothesis and choose the direction of the alternative hypothesis from the pull-down menu. Section 10.4 Hypothesis Tests for a Population Standard Deviation 2. Select the column containing the row factor in the pull-down menu Row factor in:. Select the Display means table box to use for Tukey s test. Interaction Plots In the same screen where you checked Display means table, also check Plot interactions. Select the column containing the values of response variable for the pull-down menu Responses in:.

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