文章 PASW Statistics for Windows. Version 18.0; SPSS Inc.: Chicago, IL, USA, 2009.
被如下文章引用: • TITLE: • AUTHORS:,,, • KEYWORDS: microbiota, DNA damage, comet assay, microbial fermentation, quantitative PCR • JOURNAL NAME: DOI: Sep 07, 2014 • ABSTRACT: High dietary intakes of some protein sources, including soy protein, can increase colonic DNA damage in animals, whereas some carbohydrates attenuate this. We investigated whether inulin and xylo-oligosaccharides (XOS) could be protective against DNA strand breaks by adding them to a human colonic simulator consisting of a proximal vessel (PV) (pH 5.5) and a distal vessel (DV) (pH 6.8) inoculated with human faeces and media containing soy protein. Genotoxicity of the liquid phase and microbial population changes in the vessels were measured. Soy protein (3%) was fermented with 1% low amylose cornstarch for 10 day followed by soy protein with 1% XOS or 1% inulin for 10 day.
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Inulin did not alter genotoxicity but XOS significantly reduced PV genotoxicity and increased DV genotoxicity. Inulin and XOS significantly increased butyrate concentration in the DV but not PV. Numbers of the key butyrate-producing bacterium Faecalibacterium prausnitzii were significantly increased in the PV and DV by inulin but significantly decreased by XOS in both vessels. Other bacteria examined were also significantly impacted by the carbohydrate treatments or by the vessel ( i.e., pH).
There was a significant overall inverse correlation between levels of damage induced by the ferments and levels of sulphate-reducing bacteria, Bacteroides fragilis, and acetate. In conclusion, dietary XOS can potentially modulate the genotoxicity of the colonic environment and specific bacterial groups and short chain fatty acids may mediate this.
Analytical Software at SPSS.com. PASW Statistics Base is no longer a requirement for operating other modules: they. PASW Statistics 18 Features. A new product, PASW Statistics Developer, will make it easy to work with R and share. The PASW Statistics 18 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 18 (formerly SPSS Statistics), the world's leading desktop statistical software package.
Description The PASW Statistics 18 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 18 (formerly SPSS Statistics), the world’s leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course.
With this book, you’ll learn how to describe data, test hypotheses, and examine relationships using PASW. Author Marija Norušis incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners, throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun!
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A data CD-ROM is included with this book. • Readers' questions are anticipated and clearly addressed, in special sections scattered throughout the book. • To help you focus on the contents, each chapter begins with a set of questions that are addressed in the chapter • Data sets from a variety of disciplines are included in this book. • Detailed instructions are given for obtaining all of the output shown in the book. • Statistical concept and data analysis exercises are included with each chapter.
Staff have reviewed the book for accuracy. Table of Contents PART 1. GETTING STARTED WITH PASW STATISTICS 1. Introduction About This Book Getting Started with PASW Statistics Describing Data Testing Hypotheses Examining Relationships Lets Get Started 2. An Introductory Tour of PASW Statistics Starting PASW Statistics Help Is Always at Hand Copying the Data Files Opening a Data File Statistical Procedures The Viewer Window Viewer Objects The Data Editor Window Entering Non-Numeric Data Clearing the Data Editor without Saving Changes The PASW Statistics Online Tutorial The PASW Statistics Toolbar The PASW Statistics Help System Contextual Help What’s Next? Sources of Data Know Your Data Survey Data Asking the Question Measuring Time Selecting Participants Selecting a Sample General Social Survey Random-Digit Dialing Internet Surveys Designing Experiments Random Assignment Minimizing Bias Summary What’s Next?
Exercises PART 2 DESCRIBING DATA 4. Counting Responses Describing Variables A Simple Frequency Table Sorting Frequency Tables Pie Charts Bar Charts Summarizing Internet Time Histograms Mode and Median Percentiles Summary What’s Next? How to Obtain a Frequency Table Format: Appearance of the Frequency Table Statistics: Univariate Statistics Charts: Bar Charts, Pie Charts, and Histograms Exercises 5. Computing Descriptive Statistics Summarizing Data Scales of Measurement Mode, Median, and Arithmetic Average Comparing Mean and Median Summarizing Time Spent Online Measures of Variability Range Variance and Standard Deviation The Coefficient of Variation Standard Scores Summary What’s Next?
How to Obtain Univariate Descriptive Statistics Options: Choosing Statistics and Sorting Variables Exercises 6. Comparing Groups Age, Education, and Internet Use Plotting Means Layers: Defining Subgroups by More than One Variable Summary What’s Next? How to Obtain Subgroup Means Layers: Defining Subgroups by More than One Variable Options: Additional Statistics and Display of Labels Exercises 7. Looking at Distributions Marathon Completion Times Age and Gender Marathon Times for Mature Runners Summary What’s Next?
How to Explore Distributions Explore Statistics Graphical Displays Options Exercises 8. Counting Responses for Combinations of Variables Library Use and Education Row and Column Percentages Bar Charts Adding Control Variables Library Use and the Internet Summary What’s Next? How to Obtain a Crosstabulation Layers: Three or More Variables at Once Cells: Percentages, Expected Counts, and Residuals Bivariate Statistics Format: Adjusting the Table Format Exercises 9. Plotting Data Examining Population Indicators Simple Scatterplots Scatterplot Matrices Overlay Plots Three-Dimensional Plots Identifying Unusual Points Rotating 3-D Scatterplots Summary What’s Next? How to Obtain a Scatterplot Obtaining a Simple Scatterplot Obtaining an Overlay Scatterplot Obtaining a Scatterplot Matrix Obtaining a 3-D Scatterplot Editing a Scatterplot Exercises PART 3. TESTING HYPOTHESES 10. Evaluating Results from Samples From Sample to Population A Computer Model The Effect of Sample Size The Binomial Test Summary What’s Next?
Exercises 11. The Normal Distribution The Normal Distribution Samples from a Normal Distribution Means from a Normal Population Are the Sample Results Unlikely? Testing a Hypothesis Means from Non-Normal Distributions Means from a Uniform Distribution Summary What’s Next?
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Exercises 12. Testing a Hypothesis about a Single Mean Examining the Data The T Distribution Calculating the T Statistic Confidence Intervals Other Confidence Levels Confidence Interval for a Difference Confidence Intervals and Hypothesis Tests Null Hypotheses and Alternative Hypotheses Rejecting the Null Hypothesis Summary What’s Next? How to Obtain a One-Sample T Test Options: Confidence Level and Missing Data Exercises 13. Testing a Hypothesis about Two Related Means Marathon Runners in Paired Designs Looking at Differences Is the Mean Difference Zero?