This book shows the capabilities of Microsoft Excel in teaching physical science statistics effectively. Similar to the previously published __Excel 2013 for Physical Sciences Statistics__, this book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with.
Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in physical science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, __Excel 2016 for Physical Sciences Statistics: A Guide to Solving Practical Problems__ capitalizes 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 physical science 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.

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zlib/Science (General)/Thomas J. Quirk, Meghan H. Quirk, Howard F. Horton (auth.)/Excel 2016 for Physical Sciences Statistics: A Guide to Solving Practical Problems_2803295.pdf

Quirk, Thomas J., Quirk, Meghan H., Horton, Howard F.

Adobe InDesign CC 2015 (Windows)

Springer International Publishing : Imprint : Springer

Springer Nature Switzerland AG

Springer London, Limited

Springer Nature (Textbooks & Major Reference Works), Cham, 2016

Excel for statistics, Switzerland, 2016

Excel for statistics, Cham, 2016

Heidelberg, Heidelberg, 2016

1st ed. 2016, 2016-08-03

Switzerland, Switzerland

2, 20160725

sm59704408

producers:
Adobe PDF Library 15.0

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Preface 8
Acknowledgements 10
Contents 12
Chapter 1: Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 17
1.1 Mean 17
1.2 Standard Deviation 18
1.3 Standard Error of the Mean 19
1.4 Sample Size, Mean, Standard Deviation, and Standard Error of the Mean 20
1.4.1 Using the Fill/Series/Columns Commands 20
1.4.2 Changing the Width of a Column 21
1.4.3 Centering Information in a Range of Cells 22
1.4.4 Naming a Range of Cells 24
1.4.5 Finding the Sample Size Using the =COUNT Function 25
1.4.6 Finding the Mean Score Using the =AVERAGE Function 25
1.4.7 Finding the Standard Deviation Using the =STDEV Function 26
1.4.8 Finding the Standard Error of the Mean 26
1.4.8.1 Formatting Numbers in Number Format (Two Decimal Places) 27
1.5 Saving a Spreadsheet 28
1.6 Printing a Spreadsheet 29
1.7 Formatting Numbers in Currency Format (Two Decimal Places) 31
1.8 Formatting Numbers in Number Format (Three Decimal Places) 33
1.9 End-of-Chapter Practice Problems 33
References 36
Chapter 2: Random Number Generator 37
2.1 Creating Frame Numbers for Generating Random Numbers 37
2.2 Creating Random Numbers in an Excel Worksheet 41
2.3 Sorting Frame Numbers into a Random Sequence 42
2.4 Printing an Excel File So That All of the Information Fits onto One Page 45
2.5 End-of-Chapter Practice Problems 49
Chapter 3: Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing 51
3.1 Confidence Interval About the Mean 51
3.1.1 How to Estimate the Population Mean 51
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean 52
3.1.3 Estimating the Confidence Interval the Chevy Impala in Miles per Gallon 53
3.1.4 Where Did the Number ``1.96 ́ ́ Come From? 54
3.1.5 Finding the Value for t in the Confidence Interval Formula 55
3.1.6 Using Excel ́s TINV Function to Find the Confidence Interval About the Mean 56
3.1.7 Using Excel to Find the 95% Confidence Interval for a Car ́s mpg Claim 56
3.2 Hypothesis Testing 62
3.2.1 Hypotheses Always Refer to the Population of Physical Properties That You Are Studying 63
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis 63
3.2.2.1 Determining the Null Hypothesis and the Research Hypothesis When Rating Scales Are Used 64
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean 67
3.2.3.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 67
3.2.3.2 STEP 2: Select the Appropriate Statistical Test 68
3.2.3.3 STEP 3: Calculate the Formula for the Statistical Test 68
3.2.3.4 STEP 4: Draw a Picture of the Confidence Interval About the Mean, Including the Mean, the Lower Limit of the Interval,... 68
3.2.3.5 STEP 5: Decide on a Decision Rule 68
3.2.3.6 STEP 6: State the Result of Your Statistical Test 69
3.2.3.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 69
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test 73
3.3.1 Different Ways to Accept the Null Hypothesis 74
3.3.2 Different Ways to Reject the Null Hypothesis 74
3.4 End-of-Chapter Practice Problems 75
References 79
Chapter 4: One-Group t-Test for the Mean 80
4.1 The 7 STEPS for Hypothesis-Testing Using the One-Group t-Test 80
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis 81
4.1.2 STEP 2: Select the Appropriate Statistical Test 81
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test 81
4.1.3.1 Finding the Absolute Value of a Number 81
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test 82
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E 83
4.1.6 STEP 6: State the Result of Your Statistical Test 84
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English! 84
4.2 One-Group t-Test for the Mean 85
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses? 89
4.4 End-of-Chapter Practice Problems 89
References 93
Chapter 5: Two-Group t-Test of the Difference of the Means for Independent Groups 94
5.1 The Nine STEPS for Hypothesis-Testing Using the Two-Group t-Test 95
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2 95
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group 96
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test 97
5.1.4 STEP 4: Select the Appropriate Statistical Test 97
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test 97
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test 98
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E 98
5.1.7.1 Finding the Degrees of Freedom (df) for the Two-Group t-Test 98
5.1.8 STEP 8: State the Result of Your Statistical Test 99
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English! 99
5.1.9.1 Writing the Conclusion of the Two-Group t-Test When You Accept the Null Hypothesis 100
5.1.9.2 Writing the Conclusion of the Two-Group t-Test When You Reject the Null Hypothesis and Accept the Research Hypothesis 101
5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30 104
5.2.1 An Example of Formula #1 for the Two-Group t-Test 105
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30 112
5.4 End-of-Chapter Practice Problems 118
References 121
Chapter 6: Correlation and Simple Linear Regression 122
6.1 What Is a ``Correlation? ́ ́ 122
6.1.1 Understanding the Formula for Computing a Correlation 126
6.1.2 Understanding the Nine Steps for Computing a Correlation, r 127
6.2 Using Excel to Compute a Correlation Between Two Variables 129
6.3 Creating a Chart and Drawing the Regression Line onto the Chart 134
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points 136
6.3.1.1 Drawing the Regression Line Through the Data Points in the Chart 140
6.3.1.2 Moving the Chart Below the Table in the Spreadsheet 142
6.3.1.3 Making the Chart ``Longer ́ ́ So That It Is ``Taller ́ ́ 143
6.3.1.4 Making the Chart ``Wider ́ ́ 143
6.4 Printing a Spreadsheet So That the Table and Chart Fit onto One Page 144
6.5 Finding the Regression Equation 146
6.5.1 Installing the Data Analysis ToolPak into Excel 147
6.5.1.1 Installing the Data Analysis ToolPak into Excel 2016 147
6.5.1.2 Installing the Data Analysis ToolPak into Excel 2013 148
6.5.1.3 Installing the Data Analysis ToolPak into Excel 2010 149
6.5.1.4 Installing the Data Analysis ToolPak into Excel 2007 149
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression 150
6.5.2.1 Finding the y-Intercept, a, of the Regression Line 154
6.5.2.2 Finding the Slope, b, of the Regression Line 154
6.5.3 Finding the Equation for the Regression Line 155
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value 155
6.6 Adding the Regression Equation to the Chart 156
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table 159
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet 159
6.8.1 Printing Only the Table and the Chart on a Separate Page 160
6.8.2 Printing Only the Chart on a Separate Page 160
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page 161
6.9 End-of-Chapter Practice Problems 161
References 166
Chapter 7: Multiple Correlation and Multiple Regression 168
7.1 Multiple Regression Equation 168
7.2 Finding the Multiple Correlation and the Multiple Regression Equation 171
7.3 Using the Regression Equation to Predict FROSH GPA 175
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression 175
7.5 End-of-Chapter Practice Problems 179
References 184
Chapter 8: One-Way Analysis of Variance (ANOVA) 185
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA) 186
8.2 How to Interpret the ANOVA Table Correctly 190
8.3 Using the Decision Rule for the ANOVA F-Test 190
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test 191
8.4.1 Comparing Brand A vs. Brand C in Miles Driven Using the ANOVA t-Test 192
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-Test 193
8.4.1.2 Stating the Decision Rule for the ANOVA t-Test 193
8.4.1.3 Performing an ANOVA t-Test Using Excel commands 194
8.5 End-of-Chapter Practice Problems 196
References 201
Appendices 202
Appendix A: Answers to End-of-Chapter Practice Problems 202
Appendix B: Practice Test 235
Appendix C: Answers to Practice Test 244
Appendix D: Statistical Formulas 254
Appendix E: t-Table 256
Index 257

This book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isnĺlt your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you. Excel is an effective learning tool for quantitative analyses in environmental science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Physical Sciences 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 2016 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 physical science 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. Includes 165 illustrations in color Suitable for undergraduates or graduate students Prof. Tom Quirk spent six years in educational research at The American Institutes for Research and Educational Testing Service. He is Professor of Marketing in the Walker School of Business & Technology at Webster University in St. Louis, Missouri (USA). 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 MBA from The University of Missouri-St. Louis. Dr. Meghan Quirk holds a Ph. D. in Biological Education and an M.A. in Biological Sciences from the University of Northern Colorado (UNC) and a B.A. in Biology and Religion at Principia College in Elsah, Illinois. She has co-authored an article on shortgrass steppe ecosystems in Photochemistry & Photobiology. She was a National Science Foundation Fellow GK-12, and currently teaches science in Bailey, Colorado. Howard F. Horton holds an MS in Biological Sciences from the University of Northern Colorado (UNC) and a BS in Biological Sciences from Mesa State College. He has worked on research projects in Pawnee National Grasslands and Long-Term Ecological Research at Toolik Lake, Alaska. He has co-authored articles in The International Journal of Speleology and <The Journal of Cave and Karst Studies. He was a National Science Foundation Fellow GK-12. He is currently the Angler Outreach Coordinator with Colorado Parks and Wildlife

Front Matter....Pages i-xv
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean....Pages 1-20
Random Number Generator....Pages 21-34
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing....Pages 35-63
One-Group t-Test for the Mean....Pages 65-78
Two-Group t-Test of the Difference of the Means for Independent Groups....Pages 79-106
Correlation and Simple Linear Regression....Pages 107-152
Multiple Correlation and Multiple Regression....Pages 153-169
One-Way Analysis of Variance (ANOVA)....Pages 171-187
Back Matter....Pages 189-246

2016-11-20