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77 Cards in this Set

  • Front
  • Back
Collections of ovservations (such as measurements, genders, survey responses)
Data
The sciennce of planning studies and experiments, obtaining data, and then organizaing, summarizing, presenting, analyzing, interpreting and drawing conclusions based on the data
Statistics
the complete collection of all individuals (scores, people measurements, and so on) to be studied. The cllection is complete in the sense that i includes all of the individuals to be studied.
Population
The collection of data from every member of the population.
Census
A subcollection of members selected from a population
Sample
KEY CONCEPTS:
Sample data must be collected in an appropriate way, such as through a process of random selection

If sample data are not collected in an appropriate way, the data may be so completely useless that no amount of statistial torturing can salvage them.
Key Concept
5 factors in statistics to consider:
Context of the data, source of the data, sampling method, conclusions, practical implications
A sample in which the responsdents of the study ecidd wheteher to be included or not.
Voluntary response sample. Self selection bias
Associations between two variables
Correlation
What is a voluntary response sample?
A voluntary response sample are subjects who volunteer to participate in the study
Why is a voluntary response sample generally not suitable for a statistical study?
Because the samples are biased and may or may not chose to participate if they don't think it is benefited to them.
What is the difference between statistical significance and practical significance?
Statistical significance is when the the numbers or findings of the data is effective and is positive of the outcome and prictical significance is common sense might indicate that the final outcome is not enough to justify the use of the product.
Why is it important to understand the context of the data?
You have to know what you are trying to get out of the study.
A numerical measurement describing some characteristic of a population
Parameter
A numerical measurement describing some characteristic of a sample
Statistic
Parameters are based on the entire _______, whereas, statistics are based on a ______ of the study. For example, 55% of the total 100 senators is a parameter and 57% of 2.3 million US adults is a statistic
population. Sample
This data consists of numbers rerpresenting counts or measurements.
Quantitative data
This data consists of names or labels that are not numbers representing counts or measurements
Categorical
This data results when the number of possible values is either a finite number or a countable number.
Discrete
This 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 data
Discrete data is the number of eggs an hen lays.
Continuous data is the amount of milk cows can yield over a certain time period. 5 eggs or 546.5654 liters of milk
Info
In grammer we use "fewer" for descrete amounts and "less" for continuous amounts. We drank fewer cans of cola, in the process we drank less cola
info
A measurement that is characterized by data that consists of names, labels or categories only. The data cannot be arranged in an ordering scheme, such as low to high. Yes/no/undecided. Political party affiliation.
Nominal level of measurement
This level of measurement can be arranged in some order but differences (subtraction) b/t dta values either cannot be dteremined or are meaningless. Examples: Coarse grades, ABCDF.. There is ordering hiarchy but there is no difference that can be found. Ranking systems of which school is number 1
Ordinal level of measurement
This measurement is like the ordinal level, with additional property that the difference between any two data values is meaningfull. Howeer, data at this level do not have a natural 0 starting point. Body temperature
interval level of measurement
This measurement is the interval level with the additional property that there is also a natural zero starting point. Distances traveled by cars (0 km represents no distance traveled and 400km is 2x as far as 200 km. or prices of college textbooks $0 is no cost and $100 is 2x as much as $50 text book
ratio level of meaturement
Which level of measurement is used in distances
ratio
Which level of measurement is used in body temperatures
interval
Which level of measurement is used in rankings
ordinal
Which level of measurement is used in categories such as eye colors
nominal
A sample in which the respondents themselves decide wether to be included.
Mail in polls, polls conducted through the internet, telephone polls
Voluntary response sample
Correlation does not imply causality
info
It is better to take measurements yourself then to ask subjects to report the results
info
Examples of Bad sample. Voting Behavior. OUt of 1002 eligible voters were surveyed, 70% of them said they had voted in a recent presidential election however voting records showed only 61% voted. Small sample groups. I
Info
Some studies are misleading or unclear percentages. Kee pin mind that 100% of some quantity is all of it. Fi there are references made to percentages that exceed 100%, such references are often on justified.
Info
Percentage of: finding a percentage of an amount
6% of 1200 responses
6/100x1200=72
Fraction to percentage->
3/4=
3 divided by 4 x100=75%
Decimal to percentage: convert decimal to percentage
.25
.25 x100=25%
Percentage to decimal:
85%
85/100=0.85
If survey questions are not wordd carefully the results of a study can be misleading
Vote on the following: too little money is being spent on welfare.
Too little money sis being spent on assistance ot hte poor.
Effect of the order of questioning?
would you say that traffic contributes more or less to air pollution than industry? Or visa Versa?

Which ever term is presented first can usually be keyed on. voted more
A nonresponse occurs when someone either refuses to respond to a survey question or is unavialable
info
Missing data. Results can be dramatically affected by missing data. Sometimes sample data values are missing because of random factors such as subjects dropping out of a study for reasons unrelated to the study.
info
Statistics can be be neglected due to some parties with interests to promote will sponsor studies and influence the results
info
Precice numbers can sku the numbers of what it really is. For example 1,234,023 of househoulds in the US, the number of households should state approximately.
info
This study we observe and measure specific characteristics but we don't attempt to modify the subjects being studied.

Observational or experiment
Observational
We apply some treatment and then proceed to observe its effects on the subjects.

Observational or experiment
Experiment
subjects in experiments are called
experimental units
Observational studies are when tolls are surveyed.
Experiments are a pploied with treatment
Sample of n subjects is selected in such a way that every possible sample of the same size n has the same chance of being chosen.
Simple random sample
This sample is whem members from the population are selected in such a way that each individual member in the population has an equal chance of being selected
random sample
This sample involves selecting members from a population in such a way that each memmber of the pouplation has a known chance of being selected.
Probability sample
This sample is selecting some starting point and then select every kth such as every 50th element in the population.
Systematic
This sample we use reults that are very easy to get
Convenience sampling
Samples in which we subdivide the population into at least two different subgroups or starta so that subjects within the same subgroup share the same characteristics such as gender or age bracket, then we draw a sample from each subgroup or stratum.
Stratified
This sample we subdivide the population area into sections, then randomly select some of those sections, and then choose all the members from those selected sections.
clusters
Each member of the population has an equal chance of being selected. Computers are often used to generate these.
A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
Random
a sample of N subjects is selected in such a way that every possible sample of hte same size N has the same chance of being chosen.

A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
B.
Select some starting point then select every number of an element of a population.. Like mulitples of 3.
A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
c.
Use results that are easy to get.

A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
D.
Subdivide the population into at least two different subgroups so that subjects within the same subgroup share the same characteristics then draw a sample from each subgroup.

A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
E.
Divide the poulation into sections then randomly select some of those sections and then choose all members from those selected clusters.

A. Random
B. simple random
C. systematic
D. Convenience
E. Stratified
f. Cluster
F.
In this study data are observed, measured and collected at one point in time
Cross-sectional study
In this study, data is collected form the past by going back in time through examination of records interviews and so on
Retrospective
In this study, data is collected in the future from groups charing comon factors, cohort
Prospective
This is used when subjects are assigned to different groups through a process of random selection
Randomization
This type of experiment is used in a repitition of an experiemtn on more than one subject
replication
this type of experiment is a technique in whish the subject doesn't know whether he or she is receiving a treatment or a placebo
Blinding
This is when neither the subjects nor the pollers know whom is receiving the placebo or the treatment.
Double blind
This occurs in an experiment when you are not able to distingquish among the effects of different factors. Results of experiments are sometimes ruined because of this. For example. Treating only a group of women and giving a placebo to only the men. Don't know wheter the treatment or the sex of the subjects causes the positive results
Confounding
A design in which, we Assign subjects to differet treatment groups through a process of random selection
Completely randomized experimental design
This design is when you have two groups. Group a are similar with characteristics and group B are similar with characteristics. and you randomly select people from each group
Radomized block design
Which Design. Carefully assign subjects to different treatment groups, so that those given each treatment are similar in the ways that are important to the experiment. Example. Two 27 yo males who smokes and drinks heavily and consumes salt and fat. One is treatment and other is placebo
Rigorously controlled design
Which Design. Compare exactly two treatment groups by using subjects matched in pairs that are somehow related or have similar characteristics. Twins in the study. One using crest toothpaste and the other using a generic.
Matched pairs design
Three important considerations in the design of experiments are the following:
use radomization to assign subjects to different groups.
use replication by repeating the experiment on enough subjets so that effects of treatments or other factors can be clearly seen.
Control the effects of variables by using such techniques as bllinding and a completely radomized experimental design
The difference betwen a sample result and the true population result such an error results from chance sample fluctuations
sampling errors
this error occurs when the sample data are incorrrectly collected, recorded, or analyzed (such as by selecting a biased sample, using a defective meausrement instrument, or copying hte data incorrectly.)
non sampling data