| Term |
 |
|
| Define |
|
|
| Data |
Observations (such as measurements, genders, survey responses) that have been collected |
| Statistics |
A collection of methods for planning experiments, obtaining data and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data |
| Population |
The complete collection of all elements (scores, people, measurements, and so on) to be studied |
| Population |
it includes all subjects to be studied |
| Census |
The collection of data from every member of the population |
| Sample |
A subcollection of members selected from a population |
| Sample data |
must be collected in an appropriate way, such as through a process of random selection |
| If sample data are not collected in a appropriate way, |
the data may be so completely useless that no amount of statistical torturing can salvage them |
| TYPES OF DATA??? |
Parameter,Statistic , |
| Parameter |
A numerical measurement describing some characteristic of a population. |
| Parameter |
all of those votes to be the population considered, When Lincoln was first elected, he received 39.82% of the 1,865,908 votes cast which is 29.825. |
| Statistic |
A numerical measurement describing some characteristic of a sample |
| Based on a sample |
of 877 surveyed executives, it was found that 45% of them would not hire someone with a typographical error on their job application |
| Quantitative data |
Data consists of numbers representing counts or measurement |
| Quantitative data |
weights of supermodels |
| Interval level of measurement |
Temperature, Years |
| Interval level of measurement |
Data that can be arranged in order and for which differences between data values are meaningful |
| Interval level |
shoe sizes [US vs Europe] and temperature |
| Interval data |
can be either discreet or continuous |
| Ratio level of measurement |
Data that can be arranged in order, for which differences between data values are meaningful, and there is an inherent zero starting point. |
| Ratio level of measurement |
differences and ratios are meaningful |
| Ratio level of measurement |
prices of textbooks; $50 is half of $100 |
| Ratio level of measurement |
Height of students |
| Ratio data |
is continuous. |
| Ratio level of measurement |
HIGHEST LEVEL OF DATA |
| Ratio level of measurement |
can be either discreet or continuous. |
| Quantitative (interval and ratio) data |
can be further distinguished between discrete and continuous. |
| Discrete Data |
Data that results when the number of possible values is either a finite number or a “countable” numbers. |
| Discrete Data |
Counting-type things |
| Discrete Data |
number of eggs that hens lay |
| Continuous (numerical) Data |
thickness of paper; measurement of weight |
| Continuous (numerical) Data |
Results from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps. |
| Continuous (numerical) Data |
amounts of milk from cows |
| Qualitative (or categorical or attribute) data |
Can be separated into different categories that are distinguished by some nonnumerical characteristics. |
| Continuous (numerical) Data |
The genders (male/female) of professional athletes |
| Nominal Level of Measurement |
Characterized by data that consists of names, labels, or categories only |
| Nominal Level of Measurement |
Lowest form of data. Has groups, but no ordering to the groups |
| Nominal Level of Measurement |
cannot be arranged in an ordering scheme (such as low to high) |
| Nominal Level of Measurement |
Survey responses of yes, no, and undecided |
| Nominal Level of Measurement |
Colors of cars driven by college students (red, black, blue, etc. |
| Ordinal Level of Measurement |
(Categories & groups, but with some natural order to the groups.) |
| Ordinal Level of Measurement |
Course grades – Grades of A, B, C, D, or F |
| Ordinal Level of Measurement |
Ranking cities; those ranked 1st, 2nd, 3rd, etcBut, the differences between ranks are meaningless |
| Money and Counting are |
Discrete |
| Temperature is |
Interval |
| Ages are |
usually Discrete |
| Man on the street samples are |
always convenience sampling |
| Misuses of Statistics |
self-selected surveyBad samplesSmall samplesMisleading graphsPictographsLoaded Questions |
| Misuses of Statistics |
Order of Questions |
| Misuses of Statistics |
Precise NumbersPartial picturesDeliberate Distortions |
| Randomness |
typically plays a critical role in determining which data to collect. |
| Observational Study |
Observing and measuring specific characteristics without attempting to modify the subjects being studied. (Control group) |
| Cross Sectional Study |
Data are observed, measured, and collected at one point in time. |
| Retrospective (or Case Control) Study |
Data are collected from the past by going back in time. |
| Prospective (or Longitudinal or Cohort) Study |
Data are collected in the future from groups (called cohorts) sharing common factors. |
| Experimental |
Apply some treatment and then observe its effects on the subjects. (Experimental group.) Doing something to affect what happens. |
| Experimental Key Elements |
Control, Replication, Randomization |
| control |
Effects of variables through: blinding, blocks, completely randomized, experimental design, rigorously controlled experimental design |
| Confounding |
Occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors. |
| Blinding |
Subject doesn't know if he or she is receiving a treatment or placebo |
| Double-blind |
Neither the subject nor the experimenter knows whether treatment or placebo is being administered |
| Blocks |
Groups of subjects with similar characteristics |
| Completely Randomized Experimental Design |
Subjects are put into blocks through a process of random selection |
| Rigorously Controlled Design |
Subjects are very carefully chosen so that those in each block are similar in the ways that are important to the experiment. |
| Random Sample |
Selection so that each has an equal chance of being selected |
| Simple Random Sample |
of size n |
| Systematic Sampling |
Select some starting point and then select every Kth element in the population |
| systematic sampling |
7th person of a group of 10; i.e., 7, 17, 27, 37, etc., OR every 7th person i.e., 7, 14, 21, 28, etc |
| Convenience Sampling |
Use results that are easy to get, choosing the first 10 people who get off work |
| Stratified Sampling |
Subdivide the population into at least two different subgroups that share the same characteristics, then draw a sample from each subgroup (or stratum |
| Cluster Sampling |
Divide the population into sections (or clusters); randomly select some of those clusters; choose all members from selected clusters |
| Sampling Error |
The difference between a sample result and the true population result; such an error results from chance sample fluctuations |
| Nonsampling Error |
Sample data that are incorrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective instrument, or copying the data incorrectly |
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