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Stats Exam 1 Terms
| Question | Answer |
|---|---|
| Individuals or units are | the objects (e.g. people, animals, things, etc.) described by a set of data |
| A variable is any | characteristic of an individual. It can take different values for different individuals. |
| A categorical variable | places an individual into one of several categories. To do statistics with these variables we can use counts or percentages. |
| A numerical/quantitative variable | takes numerical values for which arithmetic operations, such as adding and averaging, makes sense. |
| A response variable | measures an outcome or result of a study. |
| An observational study | observes individuals and measures variables of interest, but does not intervene to influence the responses. The purpose is to describe some group or situation |
| The population in a statistical study is | the entire group of individuals about which we want information. |
| A sample is | the part of the population from which we actually collect information and is used to draw conclusions about the whole. |
| A census is a | sample survey that attempts to include the entire population in the sample. |
| An experiment | deliberately imposes some treatment on individuals to observe their responses. The purpose is to study whether the treatment causes a change in the response. |
| The design of a statistical study is ____ if it systematically favors certain outcomes. | biased |
| Selection of whichever individuals are easiest to reach is called | convenience sampling. |
| A voluntary response sample | chooses itself by responding to a general appeal (e.g. write-in opinion polls). |
| A simple random sample (SRS) | of size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance to be in the sample actually selected (e.g. drawing names from a hat) |
| How to choose an SRS? | By a random. table of digits. stupid lots of numbers table |
| A parameter p is a | number that describes the population. A parameter is a fixed number, but in practice we don’t know the actual value of this number because we cannot access the entire population. |
| A statistic ˆp is a | number that describes a sample. The value of a statistic can be determined and is known once we have taken a sample, but its value can change from sample to sample. We often use a statistic to estimate an unknown parameter. |
| Random samples eliminate _____ from the act of choosing a sample, but they can still be wrong because of the ______ that results when we choose at random. | bias variability |
| Variability | describes how the values of the sample statistic will vary when we take many samples. Large variability means that the result of sampling is not repeatable. |
| A good sampling method has both | small bias and small variability. |
| How to calculate margin of error? | 1/ the square root of n (sample size) |
| A confidence statement has two parts: | a margin of error and a level of confidence. |
| Confidence Statement | if we chose many samples, the truth about the population would be within the margin of error 95% of the time. |
| Sampling begins with a list, called the | sampling frame |
| The sampling frame is often not an accurate or complete representation of the population. This leads to errors known as | frame errors |
| Undercoverage | If the sampling frame leaves out certain groups of people, even random samples from that frame will be biased. |
| Undercoverage Example | Using telephone directories as the frame for a telephone survey would miss everyone with an unlisted landline telephone number, who cannot afford a landline phone, and who has only a cell phone. |
| Erroneous inclusions | can occur if the frame includes units (individuals) that are not in the population of interest so that invalid units have a chance of being in the sample. |
| Multiple inclusions | occur if some population members appear multiple times in the sampling frame so that they have a higher chance of being sampled |
| processing errors — | mistakes in mechanical tasks such as doing arithmetic or entering responses into a computer |
| Response error | which occurs when a subject gives an incorrect response: – A subject may lie about her age or income or about whether she has used illegal drugs. |
| Nonresponse | is the failure to obtain data from an individual selected for a sample. Most nonresponse happens because some subjects can’t be contacted or because some subjects who are contacted refuse to cooperate. |
| To choose a stratified random sample: | a population is divided into homogeneous subgroups (strata) based on shared characteristics (e.g., age, gender, location), and then a random sample is taken from each stratum to ensure proportional representation |
| A probability sample is a | sample chosen by chance |
| A response variable is a | variable that measures an outcome or result of a study. |
| An explanatory variable | is a variable that we think explains or causes changes in the response variable. |
| The individuals studied in an experiment are often called | subjects. |
| A lurking variable is a | variable that has an important effect on the relationship among the variables in a study but is not one of the explanatory variables studied. |
| Two variables are ______ when their effects on a response variable cannot be distinguished from each other. The confounded variables may be either explanatory variables or lurking variables. | confounded |
| Experiments that study the effectiveness of medical treatments on actual patients are called | clinical trials |
| A _____ is a dummy treatment with no active ingredients. | placebo |
| double-blind | An experiment in which neither subjects nor physicians recording the symptoms know which treatment was received is called double-blind |
| The control group is the | placebo group |
| An observed effect of a size that would rarely occur by chance is called | statistically significant. |
| Good studies are _______ even when they are not experiments. | comparative |
| In a randomized comparative experiment we | compare two or more treatments, use chance to decide which subjects get each treatment, and use enough subjects so that the effects of chance are small. |
Created by:
liladdoyle