Statistics Study Guide

Data are observations that have been collected (EX. Measurements, gender, survey responses)

Statistics are a collection of methods for planning experiments, obtaining data, & then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusion based on the data.

Stats are represented by a bell curve represents any population of anything.

Census is the collection of data from every member of the population.

Observational study- we observe and measure specific characteristics, but we don’t attempt to modify the subjects being studied

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Population is the complete collection of all elements to be studied.

Parameter is a numerical measurement describing some characteristic of a sample.

What is your data set composed of?

Qualitative Data: Data are separated into different categories that are distinguished by same non-numerical characteristic.

Quantitative Data – consist of numbers representing counts or measurements.

Discrete data result when the number of possible values is either a finite number or a “countable” number (0, 1, 2, 3, etc.)

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.

Ways to classify data

Nominal data- characterized by data that consists of names labels, or categories. The data cannot be arranged in an ordering scheme (high to low, best to worst, Male or female)

Ordinal- Can be arranged in same order, but difference between data values either cannot be determine or are meaningless. (1st, 2nd, 3rd….Likert scales: 1disagree...2…3…4...5…6 agree)

Interval- distance between values becomes meaningful. However there is no natural zero starting point and ratios are meaningless. (none of the quantities are present) (Temperature 100-80=20… no mult or div)

Ratio- Just like interval data, but add a natural zero staring point. For the values at this level, differences and ratios are both meaningful. (Can mult & div…no neg numbers) (Height, weight, prices, and distance traveled, miles per hr.)

Experiment- we apply some treatment and proceed to observe its effects on the subjects.

Observational study- we observe and measure specific charactoristics, but we don’t attempt to modify the subjects being studied.

Cross-sectional study- data are observed, measured, and collected at one point in time.

Retrospective study- data are collected from the past by going back in time.

Prospective study- data are collected in the future from groups sharing common factors.

Confounding occurs in an experiment when the experimenter is not able to distinguish between the effects of different factors

Experiment we apply some treatment and then proceed to observe its effects on the subjects.

Independent variable is a value determined by the experimenter not subject.

Dependent variable is the variable that is measured in a study the idea being it depends on the level /existening of IV.

Demand characteristics are cues inadvertently provided by the researcher or research untext concerning the purposes of the study or the behavior expect from the part.

Random sample members from the population are selected in such a way that each individual member has an equal chance of being selected.

Simple random sample of size n subjects is selected in such a way that every possible sample of the same size n has the same chance of being chosen.

Systematic sampling we select some starting point and then select every kth element in the population.

Convenience sampling we simply use results that are very easy to get.

Stratified sampling we subdivide the population into at least two different subgroups that share the same character (such as gender or age bracket) then we draw a sample from each subgroup.

Cluster sampling we first divide the population area into sections (or clusters) then randomly select some of those clusters, and then choose all the members from those selected clusters.