# Data analysis 5 and 6 part 2- use slides

rename
winniesmith2's
version from
2017-10-17 08:57

## Section 1

Question | Answer |
---|---|

if our sample mean is the same then | just use the SE pooled calculation |

is the T test the same equation for even and uneven sample sizes | yes |

How do you work out degrees of freedom of 2 different sample sizes | (n1-1)+(n2-1) = n-2 |

testing the null hypothesis if t>CV | reject Ho BIGGER values are more likely to result in rejection of Ho |

testing the null hypothesis in SPSS output | -Goes an extra step -Presents the probability (p-value) the null hypothesis is true -Probabilities are always less than 1 -SMALLER values result in rejection of Ho -If alpha = 0.05 it is necessary for the p-value to be less than 0.05 to reject the null hypothesis. Look at Sig (2 tailed) column. OR if the 95% confidence interval overlaps 0. |

What does SPSS check | for equality of variance. That Group A variance is not significantly different to Group B variance. |

p value SPSS >0.05 | read equal variances assumed |

p value SPSS =0.5 | read equal variances not assumed |

What data analysis do you use in method section ( Reporting1 the results of an independent samples t-test) | A two-sample independent/ unpaired Student’s t-test assuming equal variances using a pooled standard deviation was performed to test the hypothesis that the mean number of days taken to recover from malaria with Drug A is the same as that for Drug B.” |

What data analysis do you use in results section ( Reporting1 the results of an independent samples t-test) | An independent samples t-test indicated that the difference between the two drugs was not significant t(13- (degrees of freedom)) = 1.87, p=.084, using a two tailed test. To be more complete: An independent samples t-test indicated that the difference between Drug A (Mean = 23.38, SD=4.18, N=8) was not significantly different from that of Drug B (Mean = 20.00, SD=2.45, N=7), t(13)=1.87 p=.084, using a two tailed test. |

how to convert SPSS output to a one tailed tes | Simply take the p-value (sig) associated with t from SPSS output and divide by 2 and see if its p<0.05. Then use t-table to work out calculation by hand. |

two sample t-test- cautions | -Don’t Misuse the two sample t-Test (inappropriately analysed data as two sample t-tests) such as: Comparing Paired Subjects. Comparing to a Known Value. -Preplan One-Tailed t-Tests with strong evidence -Small Sample Sizes Make Normality Difficult to Assess: Outliers can be a problem -Performing Multiple t-Tests Causes Loss of Control of the -Experiment-Wise Significance Level – more in the ANOVA lectures (comparing more than 2 groups) |

## Section 2

Question | Answer |
---|---|

What is the paired t--test | The paired t-test (also known as related measures t-test) is appropriate for data in which the two samples are paired in some way, for instance: -Pairs consist of before and after measurements on a single group of subjects or patients. -Two measurements on the same subject or entity (right and left leg, for example) are paired. |

what is paired t-test prefromed on | the difference scores. The paired t-test assumes normality of the differences. |

Null hypothesis for paired t-test | the population mean of the differences is zero |

Alternative hypothesis for paired t-test | the population mean of the differences is not zero |

t value calculation for paired t-test | mean difference/SE, Where SE = sample standard deviation (SD) divided by square root of n. |

What SE calculation do we use | SD/ square root of sample size- normal equation. |

how to calculate degrees of freedom | n-1 |

How do you use SPSS data of alpha=0.01 | it is necessary for the p-value to be less than 0.01 to reject the null hypothesis. divide sig. (2-tailed) value by 2 . |

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