# Data Lecture 5-6. Part 1

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winniesmith2's
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2017-10-16 09:56

## Section 1

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

What are the 3 types of T test | One sample t-test, two-sample t-test, paired t-test. |

One sample t-test | which is used to compare a single mean to a fixed number or “gold standard” – We covered this in first year. How many standard deviations is the mean of the sample away from the population mean value. |

two sample t-test | is used to compare two population means based on independent (unpaired) samples from the two populations or groups |

paired t-test | is used to compare two means based on samples that are paired/repeated measures (dependant) in some way |

When is t-test not approproate | when you are trying to compare more than 2 groups /samples. |

What is the purpose of the one sample t-test | The main purpose is to see whether there is evidence that the population mean from the sample is different to the specified value. Related to the one-sample t-test is a confidence interval on the mean. Calculates how many standard errors the sample mean is away from the expected value. The further away the mean is from the expected value, the larger the value of t, and the less probable it is that the real population mean could be the expected value. |

equation for one sample t-test | sample mean- population mean / standard error |

What parametric assumptions does the one sample t-test need to meet | -continuous ratio/interval data. -data that are drawn from a population that is normally distributed (test with skewness and kurtosis statistics or any statistic that tests for a normally shaped distribution). |

what assumption do you also have to check for independent t tests | The samples being compared come from populations that have the same variance |

## Section 2

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

2 sample independent/unpaired groups t-test | is used to determine whether the unknown means of two populations are different from each other based on independent samples from each population. | |

Where can the samples for a 2-sample t-test be obtained from | -a single population that has been randomly divided into two subgroups, with each subgroup subjected to one of two treatments or . -from two separate populations (e.g., male and female). -In either case, for the two sample t-test to be valid, it is necessary that the two samples are independent (i.e., unrelated to each other). | |

What are the 4 design considerations/assumtions for a 2 sample t-test | -A Two-Sample t-Test Compares Means | therefore quantitative data must be continuous e.g height, weight, IQ. -Comparing Independent Samples: the subjects are randomly selected from the same population or randomly selected from two separate populations -The t-Test Assumes Normality: assumes the variables are normally distributed and that data that are not extremely skewed (test with skewness and kurtosis statistics) -Are the Variances Equal?: samples with equal variance (although there are adjustments that deal with unequal variances) |

two-tailed tests | the population of the two groups are the same OR different | |

one-tailed tests | need good reasoning to use this. Hypothesis is directional. EX. mean of the second group is larger OR smaller. | |

In the independent t-test do you have to have the same sample size | no. you can have uneven sample sizes. | |

How can you check for normality | -First we check whether the data (recovery time in days) are normally distributed, via statistics, and separately for each group. -We get SPSS to generate skewness and kurtosis statistics in the same way as we did for the one sample t-test. | |

how to work out skewness and kurtosis | Skewness/SE skewness and kurtosis/SE kurtosis must have values between -1.96 to 1.96 to be normally distributed. If it is between values the then skewness/kurtosis is not significant. | |

look at lecture for step by step method | ok | |

What is the difference to a one sample test | We don’t know the population SD and so we are going to use BOTH sample SDs (p is used to denote pooled and SD for sample SD) to approximate to the population SD, rather than one sample. FORMULA ON LECTURE SLIDE 20 | |

when do you have to calculate standard deviation pooled | when your sample sizes are different. to use in standard error deviation pooled calculation. should be in between the 2 values- average | |

What does the SE formula change to for independent t-test | standard error pooled FORMULA SLIDE 22. used in bottom part of t-test formula . | |

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