Index Introduction to Mini Analyzing Data Confidence Intervals Hypothesis Testing Regression Videos Tips and Tricks 4 min Improve Efficiency 13 min Experimental Design 6 min Bad Data 35 min Appropriate Application Choosing Appropriate Test  Application Tools Projects Research Project Stastistics Lab Manuel   Practice  Tests & Answers Exam Help 1. Problems & Solutions 2. Statistics Reviews 3. Test Prep
 Prelude Use Statistics 101 Videos  to review difficult concepts Analyzing Data Analyzing Data 9:57 Data types, copying, coding, subsetting data  5:05 Recoding Numeric Data to Unstacking Texts 4:25 Sampling Methods  6:42  Graphing Data 9:52 Histogram 6:03 Please Research Paper Internet Library Statistics for the Behavioral Sciences Battlefield Reflections of a Life-Long Statistic Teacher Regression is a special application of inferential statistics. Regression Analysis  3:21 Regression in a general linear model 3:23 Regression 6:53 Simple Linear Regression 6:34 Correlation and Regression   Correlation Analysis  0:47 Ranking Data 2:46 AP, SAT Test Prep test and strategy help Hypothesis Testing a logical approach to inferential statistics. What is a P-Value? 5:56 A P-Value Example 9:08 Student's t-Test 9:07 What is Statistical Power? 3:59 Degrees of Freedom in Statistics 4:17 Looking up p-values in Minitab 5:40   Hypothesis Test for One Mean  1:04 VARIANCE ANALYSIS PART I  9:21 ANOVA B Interpretation and  9:20 One Way ANOVA 2:55 Basic two-way ANOVA 7:33   Inference for Medians Mann Whitney 5:18 Nonparametric Tests Three or More Medians 2:15   Control Charts 8:09 Writing Macros 7:19 AutoCreate a Script 1:42

 Problem II message: MINITAB calculates z and p simultaneously. We must redo the chapter 13 test and look for the p value. Those using Quick's worksheets should load Mini068. Others will need to load their page 68 worksheet. All MINITAB users should select Stat, Basic Statistics, and 1-Sample z. Double click on Weight to copy the file into the Variables box. Choose the Test Mean bull's eye and set the mean to 30. Set Alternative (Hypothesis) to greater than and sigma to .0653. Note: the problem's sigma of .065 was rounded. Choose OK. P = .010 and H0 is barely accepted. Problem III message: Answer this problem by hand. Chapter 15 on Hypothesis Testing of Population Proportions Problem I message: The population proportion is a type of mean so these problems use the one-sample mean test described by chapter 13 directions. Those using Quick's worksheets should load Mini096. Others should create a worksheet using 1 for those who passed and 0 for those who failed. All MINITAB users should select Stat, Basic Statistics, and 1-Sample z. Double click on Passed to copy the file into the Variables box. Choose the Test Mean bull's eye and set the mean to .86. Set the Alternative (Hypothesis) to greater than and sigma to the square root of pq which is .347. Choose OK. A z value of .82 and p value of .21 both result in accepting H0, the proportion of parts passing inspection has not increased. Problem II message: This is a 2 sample proportion test similar to those explored in chapter 14. Those using Quick's worksheets should load Mini096. Others should create a worksheet with 200 rows and 2 columns(variables). In the first column entitled Defects, enter the data for the day shift and then the data for the night shift. Enter a 0 for passes and a 1 for failed. For the source variable named Shift, enter a 0 for day shift data and a 1 for night shift data. All MINITAB users should select Stat, Basic Statistics, and 2 Samples t. Put the cursor in the box next to Samples and double click on Defects. Double click on Shift. Set the Alternative (Hypothesis) to not equal. Choose Assume equal variances and OK. MINITAB has a t value of -2.19 and Quick has a z value of -2.20. H 0 is accepted, shift defects are the same. Chapter 16 on Small Sample Hypothesis Testing Using Student's t Test Problem I message: This is an analysis of 2 independent means. It is similar to problems done earlier. Those using Quick's worksheets should load Mini100. Others should create a worksheet containing both a data variable and a source variable using procedures discussed earlier. All MINITAB users should run a 2-Sample t test using Practice Set 14 procedures. Do not assume equal variances. MINITAB's t of -4.16 and p = 0.0005 results in a rejection of H 0, sick days taken were not the same. Problem II message: This is a paired difference test. Those using Quick's data files should load Mini100. Others should add 3 variables to their page 100 worksheet, one for the efficiency before training, one for the efficiency after training, and one to store the difference. Be sure to match each employee with their before and after efficiency rating. All MINITAB users may use the MINITAB calculator to calculate the difference between employee efficiency before and after training. Choose Calc and Calculator. Use Select to copy Difference into the Store results in variable. Highlight Before and use Select to copy it into the Expression box. Choose the calculator subtraction sign. Highlight After and use Select to copy it into the Expression box. Choose OK. Choose Stat, Basic Statistics, and 1 Sample t. Double click on Difference. Choose Test mean and leave it at 0.0. Set Alternative (Hypothesis) to less than and choose OK. H0 is rejected because p = .0014 < .01. Training increased efficiency.

Statistics Software Tutorials

SPSS Statistics Video Lectures
SPSS On-Line Training Workshop
App4Stats app.