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Chapter 1 and 14
Prob & Stat Prep
| Term | Definition |
|---|---|
| Qualitative Variables | Variables that can be placed into distinct categories( like a characteristic or attribute). Data is NOT numbers. Ex. Gender, color, religious preference, geographical location. |
| Quantitative Variables | Numerical and can be ordered or ranked. Ex. Age, height, weight, body temp. |
| Discrete Variable | Variables that assume values that can be counted. Ex. # of children, # of students, # of calls received. |
| Continuous Variables | Variables that can assume an infinite number of values between any two specific values. They are obtained by measuring—often contain fractions and decimals. |
| Variable | A characteristic or attribute that can assume different values. |
| Data | the values the variables assume |
| Random Variables | variables whose values are determined by chance. |
| Data Set | a collection of data values |
| Data Value( Datum) | each value of the data set. |
| 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. |
| Sample | a group of subjects selected from a population. |
| Hypothesis Testing | a decision-making process for evaluating claims about a population based on information from samples. |
| Statistics | The science of conducting studies to collect, organize, summarize, analyze, and draw conclusions from data |
| How statistics is used in everyday life | 1. Used in fields of human endeavor-- sports, public health, and education. 2. Used to analyze the results of a survey. 3. Used as a tool in scientific research to make decisions based on controlled experiments. |
| Reasons students 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. |
| Probability | chance of an event occurring. |
| Population | consists of all subjects that are being studied. |
| Independent Variable (Exploratory) | the one that is being manipulated by the researcher. |
| Dependent Variable (Outcome, Resultant) | The variable that is being studied to see if it changes due to the manipulation. |
| True Experiments | 1. Subjects should be assigned to groups randomly. 2. Treatments should be assigned to the groups at random. |
| Quasi Experiments | when random assignments are not possible--use an intact group. Ex. In education, use certain schools or classrooms. |
| Confounding Variables | is one that influences the results of the dependent variable but cannot be separated from the independent the variable. |
| Hawthorne Effect | The subject knows that they are participating purposely so they may change their behavior in ways that affects the results of the study. |
| Control Group | The group that does not receive the treatment. Ex. No instructions about the sit-ups. Called the placebo. |
| Treatment Group | The group that receive the specific treatment. Ex. The group that gets the specific instruction about sit-ups. |
| Biased Question | A question that is ordered in such a way that a particular answer is favored over others; makes assumptions that may or may not be true. |
| Sequential Sampling | used in quality control--successive units taken from the production line and sampled to ensure the product meets the standard. |
| 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. |
| Multistage Sampling | a sampling strategy used when conducting studies involving a very large population. The entire population is divided into naturally-occurring clusters and sub-clusters, from which the researcher randomly selects the sample. |
| Ways to Collect Data | 1. Surveys 2. Surveying records 3. Direct Observation |
| Convenience Sampling | Convenient samples are used, may not be representative but can be. |
| Stratified Sampling | Obtained by dividing the population into groups( called Strata) according to some characteristic important in the study, then get the sampling from each group. |
| Cluster Sampling | Selected by dividing the population into intact groups called clusters that is representative of the population. |
| Random Sampling | selected by using chance methods or random numbers. Numbering cards or generating random number by the computer. |
| Systematic Sampling | obtained by numbering each subject of the population and then selecting every kth subject. Need to be careful numbering the subjects. |
| Data Collection Purposes | 1. To describe situations or events. 2. To help people make better decisions before acting. |
| Observation Study | The researcher merely observes what is happening or what has happened in the past and tries to draw conclusions based on these observations. Ex. Age of motorcycle owners |
| Experimental Study | The researcher manipulates one of the variables and tries to determine how the manipulation influences other variables. Ex. Types of instruction affects the number of sit-ups done. |
| Kind of Measurement Scales | how variables are categorized, counted, or measured |
| Nominal Level of Measurement | classifies data into mutually exclusive (npn-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, however, precise differences between the ranks do not exist |
| Interval Level of Measurement | Ranks data and precise differences between units of measure do exist, however, there is no meaningful (true) zero |
| Ratio Level of Measurement | possesses all the characteristics of interval measurement and there exists a true zero. In addition, true ratios exist when the same variable is measured on two different number od population |
| Telephone Surveys | Advantages- less costly, people can be more candid, not face to face Disadvantages- Not all people can be surveyed, may not be home, unlisted and cellphones, tone of interviewer may turn person being called |
| Mailed Questionnaire | Advantages- can cover a wider geographic area, less expensive to conduct, respondents can remain anonymous Disadvantages- low number of responses, inappropriate answers on questions, may be hard to understand |
| Personal Interview | Advantages- can obtain in-depth responses Disadvantages- Interviewers need to be trained, more costly, interviewer may be biased, may not be good of people interviewed |
| Types of Sampling Methods | Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling Others: Convenience Sampling Sequential Sampling Double Sampling Multistage Sampling |
| Advantages of Experimental Studies | a. Researchers can decide how to select and group subjects. b. Researchers can control or manipulate individual variables. |
| Disadvantages of Experimental Studies | a. May occur in unnatural settings (labs or classrooms). b. Hawthorne Effect-- The subject knows that they are participating purposely change their behavior in ways that it affects the results of the study |
| Advantages of Observational Studies | a. Occurs in a natural setting. b. Can be done in dangerous or unethical situations (Suicide, rape, murder, etc.) c. Can be done using variable that cannot be manipulated by the researcher. |
| Disadvantages of Observational Studies | a. A definite cause and effect situation cannot be determined since other factors have an effect on the results. b. Can be expensive and time consuming. c. May have inaccuracies in the measurements. |
| Basic Rules About Samples | 1.For researchers to make valid inferences about population characteristics the sample must be random.2 Random Sample--every member of the population must have an equal chance of being selected. 3.Unbiased Sample--a sample chosen at random from a populati |
| Reasons to use samples | a. Saves the researcher time and money b. Enables the researcher to get info that he might not be able to get otherwise. EX blood, testing products c. Enables the researcher to get more detailed info about a particular subject. |
| Incorrect Methods | 1. Ask "the person on the street" 2. Ask the question on the radio or TV and have the people listening call in to give a response--or have people respond by mail, text, tweet. |
| Correct Methods of Random Sampling-all need to have an equal chance of being selected. | 1. Number each element of the population, place numbers on cards, put cards in a hat, etc. & choose. ( cards must be well mixed) 2. Use random numbers. See figure 14-1 p 720 Table D -- Appendix C |
| Limitation of Random Sampling | If the population is extremely large, it is time consuming to number and select the samples. |
| Steps for conducting a sample survey | 1. Decide what information is needed. (9 STEPS) 2. Determine how the data will be collected (phone, mail, etc.) 3. Select information-gathering instrument or design the questionnaire if one is not available. 4. Set up a sampling list, if possi |
| Types of Surveys | 1. Interviewer--administered--requires a person to ask the questions-- in an office, on the street, mall-- face to face 2. Self-Administered--done by mail or in a classroom |
| Mistakes to avoid when writing questions | 1. Asking biased questions. 2. Using confusing words. 3. Asking double-barreled questions (2 questions). 4. Using double negatives in a question. 5. Ordering questions improperly. |
| Other factors that bias a survey. | Participant may not know anything about the subject. People respond the way the interviewer may want them to respond. People respond differently based on whether their identity is known. Time and place of the survey. Kind of questions. |
| Open-ended questions | -- lots of possible responses -- results may be varied -- you cannot summarize them |
| Closed-ended questions | -- respondent is force to choose the answers given to them |
| Misuses of Statistics 1-2 out of 7 | 1. Suspect Samples a. Too small b. Volunteer (Opinion poll) c. Convenience Sample 2. Ambiguous Averages--When the mean, median, mode, midrange show different results--one may be chosen just to make a point. |
| Misuses of Statistics 3-4 out of 7 | 3. Changing the Subject--Representing data in two different ways. Ex. 3% increase or increase of $6,000,000 4. Detached Statistics--Where no comparison is made. Ex. One brand has 1/2m fewer calories----than what??? |
| Misuses of Statistics 5 out of 7 | 5. Implied Connections--Implying connections between variables that may not be related. Uses phrases like "may help"--suggests in some people but not all. |
| Misuses of Statistics 6-7 out of 7 | 6.Misleading Graphs-- Graphs are drawn inaccurately. Pictures may be skewed. 7. Faulty Survey Questions--wording of the question can give different results. Ex. Lesson 14.2 |
Created by:
Ahuber
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