## Interpreting Quantitative Data with IBM SPSS StatisticsThe second edition of Interpreting Quantitative Data with IBM SPSS Statistics is an invaluable resource for students analysing quantitative data for the first time. The book clearly sets out a range of statistical techniques and their common applications, explaining their logic and links to the research process. It also shows how SPSS can be used as a tool to aid analysis. Key features of the second edition include: - new chapters on one-way and two-way ANOVA, the Chi-square test and linear regression. - SPSS lab sessions following each chapter which demonstrate how SPSS can be used in practice - sets of exercises and 'real-life' examples to aid teaching and learning - lists of key terms to aid revision and further reading to enhance students' understanding - an improved text design making the book easier to navigate - a companion website with answers to the labs and exercises, along with additional data sets and powerpoint slides |

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### Contents

3 | |

2 THE RESEARCH PROCESS | 32 |

PART II DESCRIPTIVE STATISTICS | 49 |

3 UNIVARIATE DESCRIPTIVE STATISTICS | 51 |

4 GRAPHICAL REPRESENTATIONS | 87 |

PART III METHODOLOGICAL TOOLS | 113 |

5 CREATING NEW VARIABLES WITH SPSS | 115 |

6 NORMAL DISTRIBUTIONS AND SAMPLING DISTRIBUTIONS | 135 |

9 HYPOTHESIS TESTING | 190 |

PART V STATISTICAL ASSOCIATION | 205 |

10 CORRELATION AND THE REGRESSION LINE | 207 |

11 TWOWAY TABLES AND THE CHISQUARED TEST | 229 |

12 TTESTS AND ANOVA | 252 |

APPENDIX | 283 |

GLOSSARY | 317 |

337 | |

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### Common terms and phrases

acceptance region analysis ANOVA answers average grade bar chart box plot calculated chapter chi-squared column command compute concept data file defined dependent variable descriptive statistics determine diagram dialog box equal estimate example explained formulated frequency table given Grade in Psychology graph groups histogram hypothesis testing IBM SPSS independent individuals inferential statistics instance interpret interval level of confidence level of measurement level of significance level of socialization margin of error Marital status married median normal curve normal distribution null hypothesis number of categories observed output percentage predicted probability of error proportion of data qualitative quantitative methods quantitative variable random sample regression line relationship represents research question sample means sampling distribution scatter diagram score shown in Figure simple random sample socialization with peers standard deviation statistical association statistically significant t-test Total two-way table valid value labels variances various whole population window women