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E-raamat: Excel 2016 for Biological and Life Sciences Statistics: A Guide to Solving Practical Problems

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  • Formaat: PDF+DRM
  • Sari: Excel for Statistics
  • Ilmumisaeg: 08-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319394893
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Excel 2016 for Biological and Life Sciences Statistics: A Guide to Solving Practical ProblemsSuurem pilt
  • Formaat: PDF+DRM
  • Sari: Excel for Statistics
  • Ilmumisaeg: 08-Aug-2016
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319394893
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This book is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical biological and life science 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 is an effective learning tool for quantitative analyses in biological and life sciences courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. However, Excel 2016 for Biological and Life 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 biological and life science problems. P

ractice 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(20)
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(1)
1.4.2 Changing the Width of a Column
5(1)
1.4.3 Centering Information in a Range of Cells
6(2)
1.4.4 Naming a Range of Cells
8(1)
1.4.5 Finding the Sample Size Using the = COUNT Function
9(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
10(3)
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
17(4)
References
20(1)
2 Random Number Generator
21(14)
2.1 Creating Frame Numbers for Generating Random Numbers
21(3)
2.2 Creating Random Numbers in an Excel Worksheet
24(2)
2.3 Sorting Frame Numbers into a Random Sequence
26(4)
2.4 Printing an Excel File So That All of the Information Fits onto One Page
30(3)
2.5 End-of-Chapter Practice Problems
33(2)
3 Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
35(30)
3.1 Confidence Interval About the Mean
35(12)
3.1.1 How to Estimate the Population Mean
35(1)
3.1.2 Estimating the Lower Limit and the Upper Limit of the 95% Confidence Interval About the Mean
36(1)
3.1.3 Estimating the Confidence Interval the Chevy Impala in Miles Per Gallon
37(1)
3.1.4 Where Did the Number "1.96" Come From?
38(1)
3.1.5 Finding the Value for t in the Confidence Interval Formula
39(1)
3.1.6 Using Excel's TINV Function to Find the Confidence Interval About the Mean
40(1)
3.1.7 Using Excel to find the 95% Confidence Interval for a Car's mpg Claim
41(6)
3.2 Hypothesis Testing
47(10)
3.2.1 Hypotheses Always Refer to the Population of People, Plants, or Animals that You Are Studying
47(1)
3.2.2 The Null Hypothesis and the Research (Alternative) Hypothesis
48(3)
3.2.3 The 7 Steps for Hypothesis-Testing Using the Confidence Interval About the Mean
51(6)
3.3 Alternative Ways to Summarize the Result of a Hypothesis Test
57(2)
3.3.1 Different Ways to Accept the Null Hypothesis
58(1)
3.3.2 Different Ways to Reject the Null Hypothesis
58(1)
3.4 End-of-Chapter Practice Problems
59(6)
References
63(2)
4 One-Group t-Test for the Mean
65(16)
4.1 The Seven STEPS for Hypothesis-Testing Using the One-Group t-Test
65(5)
4.1.1 STEP 1: State the Null Hypothesis and the Research Hypothesis
66(1)
4.1.2 STEP 2: Select the Appropriate Statistical Test
66(1)
4.1.3 STEP 3: Decide on a Decision Rule for the One-Group t-Test
66(1)
4.1.4 STEP 4: Calculate the Formula for the One-Group t-Test
67(1)
4.1.5 STEP 5: Find the Critical Value of t in the t-Table in Appendix E
68(1)
4.1.6 STEP 6: State the Result of Your Statistical Test
69(1)
4.1.7 STEP 7: State the Conclusion of Your Statistical Test in Plain English!
69(1)
4.2 One-Group t-Test for the Mean
70(6)
4.3 Can You Use Either the 95% Confidence Interval About the Mean OR the One-Group t-Test When Testing Hypotheses?
76(1)
4.4 End-of-Chapter Practice Problems
76(5)
References
80(1)
5 Two-Group t-Test of the Difference of the Means for Independent Groups
81(28)
5.1 The 9 STEPS for Hypothesis-Testing Using the Two-Group t-Test
82(9)
5.1.1 STEP 1: Name One Group, Group 1, and the Other Group, Group 2
82(1)
5.1.2 STEP 2: Create a Table That Summarizes the Sample Size, Mean Score, and Standard Deviation of Each Group
83(1)
5.1.3 STEP 3: State the Null Hypothesis and the Research Hypothesis for the Two-Group t-Test
84(1)
5.1.4 STEP 4: Select the Appropriate Statistical Test
84(1)
5.1.5 STEP 5: Decide on a Decision Rule for the Two-Group t-Test
85(1)
5.1.6 STEP 6: Calculate the Formula for the Two-Group t-Test
85(1)
5.1.7 STEP 7: Find the Critical Value of t in the t-Table in Appendix E
85(1)
5.1.8 STEP 8: State the Result of Your Statistical Test
86(1)
5.1.9 STEP 9: State the Conclusion of Your Statistical Test in Plain English!
87(4)
5.2 Formula #1: Both Groups Have a Sample Size Greater Than 30
91(7)
5.2.1 An Example of Formula #1 for the Two-Group t-Test
92(6)
5.3 Formula #2: One or Both Groups Have a Sample Size Less Than 30
98(7)
5.4 End-of-Chapter Practice Problems
105(4)
References
107(2)
6 Correlation and Simple Linear Regression
109(44)
6.1 What Is a "Correlation?"
109(7)
6.1.1 Understanding the Formula for Computing a Correlation
114(1)
6.1.2 Understanding the Nine Steps for Computing a Correlation, r
114(2)
6.2 Using Excel to Compute a Correlation Between Two Variables
116(5)
6.3 Creating a Chart and Drawing the Regression Line onto the Chart
121(10)
6.3.1 Using Excel to Create a Chart and the Regression Line Through the Data Points
123(8)
6.4 Printing a Spreadsheet So That the Table and Chart Fit Onto One Page
131(2)
6.5 Finding the Regression Equation
133(9)
6.5.1 Installing the Data Analysis ToolPak into Excel
134(3)
6.5.2 Using Excel to Find the SUMMARY OUTPUT of Regression
137(3)
6.5.3 Finding the Equation for the Regression Line
140(1)
6.5.4 Using the Regression Line to Predict the y-Value for a Given x-Value
141(1)
6.6 Adding the Regression Equation to the Chart
142(3)
6.7 How to Recognize Negative Correlations in the SUMMARY OUTPUT Table
145(1)
6.8 Printing Only Part of a Spreadsheet Instead of the Entire Spreadsheet
145(2)
6.8.1 Printing Only the Table and the Chart on a Separate Page
146(1)
6.8.2 Printing Only the Chart on a Separate Page
146(1)
6.8.3 Printing Only the SUMMARY OUTPUT of the Regression Analysis on a Separate Page
147(1)
6.9 End-of-Chapter Practice Problems
147(6)
References
152(1)
7 Multiple Correlation and Multiple Regression
153(18)
7.1 Multiple Regression Equation
153(3)
7.2 Finding the Multiple Correlation and the Multiple Regression Equation
156(4)
7.3 Using the Regression Equation to Predict FRUIT PRODUCED
160(1)
7.4 Using Excel to Create a Correlation Matrix in Multiple Regression
160(4)
7.5 End-of-Chapter Practice Problems
164(7)
References
169(2)
8 One-Way Analysis of Variance (ANOVA)
171(18)
8.1 Using Excel to Perform a One-Way Analysis of Variance (ANOVA)
173(2)
8.2 How to Interpret the ANOVA Table Correctly
175(1)
8.3 Using the Decision Rule for the ANOVA F-Test
176(1)
8.4 Testing the Difference Between Two Groups Using the ANOVA t-Test
177(5)
8.4.1 Comparing Subspecies B vs. Subspecies C in the Number of Sound Bursts per Cycle Using the ANOVA t-Test
177(1)
8.4.1.1 Finding the Degrees of Freedom for the ANOVA t-test
178(1)
8.4.1.2 Stating the Decision Rule for the ANOVA t-test
179(1)
8.4.1.3 Performing an ANOVA t-Test Using Excel Commands
179(3)
8.5 End-of-Chapter Practice Problems
182(7)
References
188(1)
Appendices
189(58)
Appendix A Answers to End-of-Chapter Practice Problems
189(34)
Appendix B Practice Test
223(10)
Appendix C Answers to Practice Test
233(11)
Appendix D Statistical Formulas
244(2)
Appendix E t-Table
246(1)
Index 247
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.
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