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E-raamat: Excel 2016 for Educational and Psychological Statistics: A Guide to Solving Practical Problems

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  • Formaat: PDF+DRM
  • Sari: Excel for Statistics
  • Ilmumisaeg: 10-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319397207
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Excel 2016 for Educational and Psychological Statistics: A Guide to Solving Practical ProblemsSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Excel for Statistics
  • Ilmumisaeg: 10-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319397207
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This book shows the capabilities of Microsoft Excel in teaching educational and psychological statistics effectively. Similar to the previously published Excel 2013 for Educational and Psychological Statistics , this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical education and psychology problems. If understanding statistics isn"t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you.Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in education and psychology courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Educational and Psychological Statistics: A Guide to Solving Practical Problems is the first book to capitalize on these improvements

by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand educational and psychological problems. Practice problems are provided at the end of each chapter with their solutions in an appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.

Introduction.- Sample size, mean, standard deviation, standard error of the mean.- Random number generator.- Confidence interval about the mean using the TINV function and hypothesis testing.- One-group t-test for the mean.- Two-group t-test of the difference of the means for independent groups.- Correlation and simple linear regression.- Multiple correlation and multiple regression.- One-way analysis of variance (ANOVA).- Appendix A.- Appendix B.- Appendix C.- Appendix D.- Appendix E.- Index.
1 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
1(22)
1.1 Mean
1(1)
1.2 Standard Deviation
2(1)
1.3 Standard Error of the Mean
3(1)
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
4(9)
1.4.1 Using the Fill/Series/Columns Commands
4(2)
1.4.2 Changing the Width of a Column
6(1)
1.4.3 Centering Information in a Range of Cells
7(1)
1.4.4 Naming a Range of Cells
8(2)
1.4.5 Finding the Sample Size Using the =COUNT Function
10(1)
1.4.6 Finding the Mean Score Using the =AVERAGE Function
10(1)
1.4.7 Finding the Standard Deviation Using the =STDEV Function
10(1)
1.4.8 Finding the Standard Error of the Mean
11(2)
1.5 Saving a Spreadsheet
13(1)
1.6 Printing a Spreadsheet
14(1)
1.7 Formatting Numbers in Currency Format (Two Decimal Places)
15(2)
1.8 Formatting Numbers in Number Format (Three Decimal Places)
17(1)
1.9 End-of-Chapter Practice Problems
18(5)
Reference
21(2)
2 Random Number Generator
23(14)
2.1 Creating Frame Numbers for Generating Random Numbers
23(4)
2.2 Creating Random Numbers in an Excel Worksheet
27(1)
2.3 Sorting Frame Numbers into a Random Sequence
28(4)
2.4 Printing an Excel File So That All of the Information Fits onto One Page
32(3)
2.5 End-of-Chapter Practice Problems
35(2)
Reference
36(1)
3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
37(30)
3.1 Confidence Interval About the Mean
37(11)
3.1.1 How to Estimate the Population Mean
37(1)
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95 % Confidence Interval About the Mean
38(1)
3.1.3 Estimating the Confidence Interval the Chevy Impala in Miles Per Gallon
39(1)
3.1.4 Where Did the Number "1.96" Come From?
40(1)
3.1.5 Finding the Value for t in the Confidence Interval Formula
41(1)
3.1.6 Using Excel's TINV Function to Find the Confidence Interval About the Mean
42(1)
3.1.7 Using Excel to find the 95 % Confidence Interval for a Car's mpg Claim
42(6)
3.2 Hypothesis Testing
48(11)
3.2.1 Hypotheses Always Refer to the Population of People or Events that You Are Studying
49(1)
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis
50(3)
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean
53(6)
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test
59(1)
3.3.1 Different Ways to Accept the Null Hypothesis
59(1)
3.3.2 Different Ways to Reject the Null Hypothesis
60(1)
3.4 End-of-Chapter Practice Problems
60(7)
References
66(1)
4 One-Group t-Test for the Mean
67(18)
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test
67(5)
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis
68(1)
4.1.2 STEP 2: Select the Appropriate Statistical Test
68(1)
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test
68(1)
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test
69(1)
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E
70(1)
4.1.6 STEP 6: State the Result of Your Statistical Test
71(1)
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English!
71(1)
4.2 One-Group t-Test for the Mean
72(6)
4.3 Can You Use Either the 95 % Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses?
78(1)
4.4 End-of-Chapter Practice Problems
78(7)
References
84(1)
5 Two-Group t-Test of the Difference of the Means for Independent Groups
85(30)
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test
86(8)
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2
86(1)
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group
86(2)
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test
88(1)
5.1.4 STEP 4: Select the Appropriate Statistical Test
88(1)
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test
88(1)
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test
89(1)
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E
89(1)
5.1.8 STEP 8: State the Result of Your Statistical Test
90(1)
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English!
90(4)
5.2 Formula #1: Both Groups Have More Than 30 People in Them
94(8)
5.2.1 An Example of Formula #1 for the Two-Group t-Test
96(6)
5.3 Formula #2: One or Both Groups Have Less Than 30 People in Them
102(13)
5.3.1 End-of-Chapter Practice Problems
110(4)
References
114(1)
6 Correlation and Simple Linear Regression
115(44)
6.1 What Is a "Correlation?"
115(7)
6.1.1 Understanding the Formula for Computing a Correlation
120(1)
6.1.2 Understanding the Nine Steps for Computing a Correlation, r
120(2)
6.2 Using Excel to Compute a Correlation Between Two Variables
122(5)
6.3 Creating a Chart and Drawing the Regression Line onto the Chart
127(10)
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points
129(8)
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page
137(1)
6.5 Finding the Regression Equation
138(10)
6.5.1 Installing the Data Analysis ToolPak into Excel
139(3)
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression
142(4)
6.5.3 Finding the Equation for the Regression Line
146(1)
6.5.4 Using the Regression Line to Predict the y-value for a Given x-value
147(1)
6.6 Adding the Regression Equation to the Chart
148(3)
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table
151(1)
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet
151(2)
6.8.1 Printing Only the Table and the Chart on a Separate Page
152(1)
6.8.2 Printing Only the Chart on a Separate Page
152(1)
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page
153(1)
6.9 End-of-Chapter Practice Problems
153(6)
References
158(1)
7 Multiple Correlation and Multiple Regression
159(20)
7.1 Multiple Regression Equation
159(3)
7.2 Finding the Multiple Correlation and the Multiple Regression Equation
162(5)
7.3 Using the Regression Equation to Predict FROSH GPA
167(1)
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression
167(4)
7.5 End-of-Chapter Practice Problems
171(8)
References
177(2)
8 One-Way Analysis of Variance (ANOVA)
179(20)
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA)
181(2)
8.2 How to Interpret the ANOVA Table Correctly
183(1)
8.3 Using the Decision Rule for the ANOVA F-Test
184(1)
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test
185(4)
8.4.1 Comparing LECTURES vs. INDEPENDENT in Their Exam Scores Using the ANOVA t-Test
185(4)
8.5 End-of-Chapter Practice Problems
189(10)
References
197(2)
Appendices
199(1)
Appendix A Answers to End-of-Chapter Practice Problems 199(35)
Appendix B Practice Test 234(11)
Appendix C Answers to Practice Test 245(11)
Appendix D Statistical Formulas 256(2)
Appendix E t-Table 258(1)
Index 259
At the beginning of his academic career, Prof. Tom J. Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service.  He then taught Social Psychology, Educational Psychology, General Psychology, Marketing, Management, and Accounting at Principia College, and is currently a Professor of Marketing in the George Herbert Walker School of Business & Technology at Webster University based in St. Louis, Missouri (USA) where he teaches Marketing Statistics, Marketing Research, and Pricing Strategies.  He has written 60+ textbook supplements in Marketing and Management, published 20+ articles in professional journals, and presented 20+ papers at professional meetings.  He holds a B.S. in Mathematics from John Carroll University, both an M.A. in Education and a Ph.D. in Educational Psychology from Stanford University, and an M.B.A. from The University of Missouri-St. Louis.
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