Embed Code - If you would like this activity on your web page, copy the script below and paste it into your web page.

Normal Size Small Size show me how

Normal Size Small Size show me how

# Biostats Test 2

### Test 2 Notes

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

What is a Statistical Inference? | A procedure by which we use information from a sample, that is drawn from a population, to reach a conclusion about the population. |

What is Estimation? | Estimation uses sample data to calculate a statistic that is an approximation of the parameter of the population from which the sample was drawn. |

What is Samples Population? | The population from which you draw your sample. |

What is Target Population? | The population you wish to make an inference about; the population you wish to generalize your results to. |

Why is Estimation useful? | Workers in the health sciences field are often interested in parameters, such as proportions or means, of different populations.It is usually not feasible (due to cost and/or time limitations) to sample the entire population even if it is finite. |

A ___________ is a single numerical value used to estimate the corresponding population parameter | Point estimate |

An ___________ consists of a range of values (with a lower and upper bound) constructed to have a specific probability (the confidence) of including the population parameter. | Interval Estimate |

An __________ is the single value computed. The __________ is the rule that that tells us how to compute the estimate | estimate, estimator |

An estimate, T, is said to be an _______ of a parameter 0 if the expected value of the estimate (T) equals 0. E(T) = 0 | unbiased estimator |

One criteria for picking the best estimator is the property of what? | Unbiasedness |

Unbiased estimates of their corresponding parameters: | difference between two sample means, sample proportion, difference between two sample proportions |

What is this:In repeated sampling from a normally distributed population with a known standard deviation, 100(1-α) percent of all intervals of the form will in the long run include the population mean mue | Probabilistic Interpretation |

Unbiased estimates of their corresponding parameters: | difference between two sample means, sample proportion, difference between two sample proportions |

What is this:In repeated sampling from a normally distributed population with a known standard deviation, 100(1-α) percent of all intervals of the form will in the long run include the population mean mue | Probabilistic Interpretation |

What is this:When sampling is from a normally distributed population with a known standard deviation, we are 100(1-α) percent confident that the single computed interval, contains the population mean mue. | Practical Interpretaion |

The ______________ is the quantity obtained by multiplying the reliability coefficient by the standard error of the mean. This quantity is also called the _______________ . | precision of the estimate, margin of error |

You cannot always assume the population is normally distribution. However, the ________ tells us that for large samples, the sampling dist. of xbar is approximately normally distributed regardless of the distribution of the individuals in the population. | Central Limit Theorem |

It is almost always the case that if you don’t know your population mean, u, (which is why we would use this estimation procedure), then you also don’t know your ______________ . | population variance |

The number of ________ for a statistic equals the number of observations minus the number of components in its calculation that need to be estimated. | degrees of freedom (df) |

How do you know if the population variances are equal? | If the larger samp.variance is more than 2x as lrg as the smlr samp. var.– then the pop. var. are un=. You don't have to use the un= var. form, for the CI around the dif. between 2 pop.means – if you encounter a ? that has unequal var.–var. are un= and th |

n*p > 5 and n*(1-p) > 5, we can consider the sampling distribution of p-hat to be close to the ______________. | normal distribution |

True or False If we fail to reject the null hypothesis then we conclude that the null hypothesis is true. | False |

In a hypothesis test, one way to reject the null hypothesis is to see if the p-value is less than or equal to ________. | Aplha |

When estimating the population mean, we use the ____distribution when the population variance is known and the _____ distribution when the population variance is unknown. | z, t |

The ______gives us the probability associated with obtaining the computed test statistic or one more extreme if the null hypothesis is true. | p-value |

Ture or FalseHolding everything else constant, a 99% confidence interval is wider than a 95% confidence interval. | True |

The probability of rejecting a null when it is actually true is called _______; this is a Type ___ error. | aplha, Type 1 |

As the sample size ________ the standard error of the estimate decreases. | increases |

True or FalseWhen evaluating a given hypothesis, a confidence interval and hypothesis test on the same data won't always give you the same conclusion. | True |

The ____ hypothesis is always a statement of equality. | Null |

Power is the term for the probability of: | Rejecting a null hypothesis when it is actually false. |

True or False Using the same data, a p-value from a two tailed test is larger than a p-value based on a one-tailed test. | True |

Holding everything else constant, as the sample size increases, the width of the confidence interval: | Decreases |

What is the general form of a CI__________+/-________________*____________ _____________________________ | estimator+/-reliability coefficient/standard errorMargin of error |

When calculating a confidence interval for the population mean and the population variance is unknown you use ____________ table. | t |

What can we assume when p<aplha | That the variences are unequal and reject the null |

What can we assume when p>aplha | That the variences are equal and fail to reject the null |

When you see an equal sign what can you assume? | That it is a two tailed test and that to find the p-value you would have to divide by 2 |

When you see a greater than or less than sign what can you assume? | That the table is a one tailed test. |

Created by:
ladougharty