## Statistics for NursingProfessional nurses must be able to critique and understand the strengths and weakness of statistical design and analysis in order to develop evidence-based practices in a clinical setting. Statistics for Nursing: A Practical Approach teaches entry-level nursing students the selection, application, and evaluation of statistical analysis techniques in addition to how to evaluate and apply the results derived from this analysis. Written in a clear, straightforward manner, this comprehensive text includes chapter objectives, a clinical research focus, a research application box, chapter summaries, key terms for each chapter, review questions, application exercises, and much more. |

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### Contents

How to Figure Things Out | 1 |

Will my Audience be Able to See What the Data is Saying? | 13 |

What Does the Data Tell me? | 29 |

Is Your Instrument Good Bad or Ugly? | 47 |

Does the Sample Represent the Population? | 63 |

What is my Research Idea? | 75 |

So How Many Subjects do I Need? | 87 |

Is There a Difference? | 105 |

How do I Compare the Dependent Variable Means from More than Two Samples? | 141 |

What about Looking for a Relationship Between Two Variables in the Same Sample? | 157 |

Making the Public Announcement | 171 |

References | 185 |

Practice Article Doering et al Using What You Know | 187 |

Practice Article Chang et al Using What You Know | 209 |

Tables for Reference | 227 |

237 | |

How Can I Find a Difference in the Two Sample Means if my Dependent Variable is at the Interval or Ratio Level? | 121 |

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alpha alternative hypothesis analysis ANOVA associated BDI-PC BDI-SF Beck Depression Inventory CABG CABG surgery calculate central tendency chance chi-square test clinical concepts correlation coefficient cumulative cutoff degrees of freedom dependent variable detect determine diagnosis disease effect effect size epinephrine exam example exposure fail to reject frequency distribution GCS score HDRS hospital identify incidence rate increase instrument interval level of measurement look major depression measure of central median negative predictive value nonprobability sampling normal distribution nosocomial infection null hypothesis nursing research observation outcome p-value participate patients percentage physical restraints population postoperative prevalence probability random reject the null relationship relative frequency relative risk reliability REVIEW QUESTIONS screening test selected sensitivity shown in Figure specificity standard deviation statistically significant STATISTICIAN Brendan Heavey student t-test subjects t-test tion total number type one error type two error unplanned extubation unplanned extubation group validity variance