|Statistics||the science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data.|
|How are statistics used in everyday life?||1. in fields of human endeavor – sports and public health
2. to analyze the results of a survey
3. as a tool in scientific research to make decisions based on controlled experiments.
4. Operations research, quality control estimation, and predictions
|Reasons to study statistics.||1. To be able to understand statistical studies.
2. To be able to conduct research, design experiments, make predictions, and communicate results.
3. To become better consumers.
|Variable||a characteristic or attribute that can assume different values.|
|Data||the values the variables assume.|
|Random Variables||variable whose values are determined by chance|
|Data Set||a collection of data values|
|Data Value (Datum)||each value of the data set|
|Probability||the chance of an event occurring|
|Population||consists of all subjects that are being studied|
|Sample||a group of subjects selected from a population|
|Descriptive Statistics||consists of the collection, organization, summarization, and presentation of data.|
|Inferential Statistics||consists of generalizing from samples to populations, performing estimations and hypothesis tests, determining relationships among variables,and making predictions.|
|Quantitative Variables||variables that are numerical and can be ordered and ranked.|
|Discrete Variables||Variables that assume values that can be counted.|
|Continuous Variables||Variables that can assume an infinite amount of values between any two specific values. (Usually obtained by measuring – fractions or decimals)|
|Find the boundaries: .43 sec||.425 – .435 seconds|
|Nominal Level of Measurement||classifies data into mutually exclusive (non-overlapping) exhausting categories in which no order or ranking can be imposed on the data.|
|Ordinal Level of Measurement||classifies data into categories that can be ranked and precise differences between the ranks do exist.|
|Interval Level of Measurement||Ranks data and precise differences between units of measure do exist and there exists a true zero. -IQ tests, SAT scores, Temperature.|
|Ratio Level of Measurement||possesses all the characteristics of the interval measurement and there is no true zero. -height, weight, age, time, salary.|
|What are the two purposes of data collection?||1. To describe situations or events
2. To help people make better decisions before acting
|3 Ways to Collect Data||Surveys, Mailed Questionnaire, Personal Interview|
|Telephone Surveys||Advantage-Less costly,people can be more candid, not face to face.
Disadvantages- Not all people can be surveyed, may not be home,unlisted, or cell phones.
|Mailed Questionnaire||Advantages – can cover a wider geographic area, less expensive to conduct, respondents can remain anonymous.
Disadvantages – low # of responses or, inappropriate or confusing answers.
|Personal Interview||Advantages- can obtain in-depth response.
Disadvantages- Interviewers need to e trained, more costly, interviewer may be biased, may not be a good sampling of people interviewed.
|Random Sampling||a sampling technique where you randomly select a group of subjects (a sample) for study from a larger group (a population).
Ex: Drug test at school where they randomly call 350 of the 1000 students to test.
|Systematic Sampling||a sampling technique where you take a random sample of the population by using every kth variable. Ex: When choosing homecoming candidates every 40th person is chosen.|
|Stratified Sampling||a sampling technique where you take samples from each stratum or sub-group of a population. Ex: Out of all the teachers in a school you question the math department teachers on if students should have homework or not.|
|Cluster Sampling||a sampling technique where the entire population is divided into groups, or clusters, and a random sample of these clusters are selected.|
|Margin of Error Interval||p+-1/square root(n)|
|Sequential Sampling||used in quality control–successive units taken form the production line and sampled to ensure the product meets the standards|
|Double Sampling||a large population is given a questionnaire to see who meets the requirements for the study. After reviewing the questionnaire a smaller population is defined and a sample is chosen from this population.|
|Experimental Studies||the researcher manipulates one of the variables and tries to determine how the manipulation influences other variables|
|Advantages of Observational Studies||1. Occurs in a natural setting||2. Can be done in dangerous or unethical situations (suicide, rape, murder, etc)||3. Can be done using variables that cannot be manipulated by the researcher.|
|Disadvantages of Observational Studies||1. A definite cause and effect situation cannot be determined since other factors have an affect on the results||2. Can be expensive and time consuming||3. May have inaccuracies in the measurements|
|Advantages of Experimental Studies||1. Researchers can decide how to select and group subjects||2. Researchers can control or manipulate individual variables|
|Disadvantages of Experimental Studies||1. May occur in unnatural settings(labs or classrooms)||2. Hawthorne Effect||3. Confounding Variables|
|5 Uses of Statistics||1. To describe data.
2. To compare two or more data sets.
3. To determine if variables are related.
4. To test hypothesis.
5. To make estimates about population variances.
|7 Misuses of Statistics||1. Suspect Samples
2. Ambiguous Averages
3. Changing the subject
4. Detached Statistics
5. Implied Connections
6. Misleading Graphs
7. Faulty Survey Questions.
|Things that make a survey question bad||1. Asking biased questions
2. using confusing words
3. asking double barreled questions
4. using double negatives in a question
5. ordering questions improperly
|Problems for getting random samples||by random sampling you may not get a broad enough population and create a biased response/result.|
|Problems for getting systematic samples||Systematic samples are every kth variable so can miss patterns in the population that you will not get from every kth variable.|
|Independent Variable (Explanatory)||the one that is being manipulated by the researcher|
|Dependent Variable (Outcome, Resultant)||the varibale that is being studied to see if it changes due to its manipulation|
|True Experimental Study||Subjects should be assigned to groups randomly and treatments should be assigned to the groups at random|
|Quasi- Experimental Study||when random assignments are not possible–use an intact group|
|Confounding Variable||variable that influences the results of the dependent variable but cannot be separated from the independent variable|
|Hawthorne Effect||the subject knows that they are participating and purposely change their behavior in ways that it affects the results of the survey|
|Control Group||the group that does not receive the treatment|
|Treatment Group||the group that receives the specific treatment|
|Biased Question||a question that pushes sample to respond the way the researcher wants them to.|
|Unbiased Question||a question that is fair and provides a random response that is not altered by the wording of the question being asked.|
|Multistage Sampling||a combination of sampling methods where you divide a population into clusters then pick at random one of those, and get more specific as you move on. (states,regions,large cities and small towns, districts, streets, families who live on those streets.)|
|Qualitative Variables||variables that can be placed into distinct categories(characteristics not numbers)|
|Margin of Error||+-1/Square root(n)|
|Observational Studies||the researcher merely observes what is happening or what has happened in the past and tires to draw conclusions based on these obeservations|