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School: California State University - Fullerton
Department: Child Development
Course: Inquiry & Methodology in Child Development
Professor: Sarana roberts
Term: Fall 2016
Cost: 50
Name: CAS 301 Exam 2 Study Guide
Description: Exam 2 Study Guide Dr. Sarana Roberts
Uploaded: 10/25/2016
26 Pages 240 Views 0 Unlocks

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The first thing the researcher must do is explicitly determine the research objectives: what is it that he or she wishes to know?

○ Why conduct surveys?

CAS 301 Exam 2 Study Guide 1. Difference Between a Sample and a Population ○ A population is the entire group you want to study ■ In nearly every case, it is not feasible to study/survey the entire population ○ A sample is groups or individuals chosen from the population; allows us Don't forget about the age old question of which of the following is every society's most important primary group?
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Don't forget about the age old question of mc = atc at the minimum of _________ .
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to make generalizations about the population 2. Issues with Sampling ○ Simple random sampling ■ May cost more; may be difficult to get full list of all members of any population of interest ○ Stratified random sampling ■ May cost more; may be difficult to get full list of all members of any population of interest ○ Cluster sampling ■ May cost more; may be difficult to get full list of all members of any chosen cluster ○ Haphazard sampling ■ Likely to introduce bias into the sample; results may not generalize to intended population ○ Purposive sampling ■ Likely to introduce bias into the sample; results may not generalize to intended population ○ Quota sampling ■ Likely to introduce bias into the sample; results may not generalize to intended population; no method for choosing individuals in subgroups 3. Symbols ○ Correlation = R, r○ Effect size = ES, d, R, r ○ Mean = M, X, x ○ Standard deviation = SD, s ○ Variance = s2 ○ Sample size = n ○ Proportion of sample elements that have a particular attribute = p ○ Degrees of freedom = df 4. Equations/Formulas for Inferential Statistics ○ Regression ■ General: Y = a + bX ■ Multiple: Y = a + b1X1 + b2X2 + … + bnXn ○ T ■ Group difference / within-group variability ■ ○ Degrees of Freedom ■ N - 1 (one mean) ■ N1 + N2 - 2 (two means) ○ Effect Size ■ Effect size r = √t2 t2 + df ○ Cohen’s D ■ 5. Descriptive vs. Inferential Statistics○ Inferential ■ Examine multiple samples in order to make generalizations about the population ■ Estimation of parameter(s) 1. Indicates how representative the sample is of the population ■ Testing of statistical hypotheses 1. Correlation 2. Regression 3. t test 4. F-test (ANOVA) ○ Descriptive ■ Tells you about the sample in terms of central tendency (mean, median, and mode), standard deviation, and variance 6. Basic Types of Inferential Statistics and When They’re Used ○ Correlation pg. 245 ■ Correlate individual scores when you do not have distinct groups of subjects ■ Individuals are measured on two variables that each have numeric value ■ Ex. examining the relationship between variable x and variable y ○ Regression ■ Calculations are used to predict a person’s score on one variable when that person’s score on another variable is already known ■ “Prediction equations” that are based on known information about the relationships between the two variables ■ General form: Y = a + bx 1. Y = the score we wish to predict2. X = the known score 3. A = the constant 4. B = a weight adjustment factor that is multiplied by X (the slope of the line) ■ t test 1. Looks at two groups to find if there is a difference in their averages 2. One tail (directional hypothesis) or two-tail ■ F-test (ANOVA) 1. Looks at 3+ groups to see if there are statistically significant differences in their averages 7. Basic Types of Descriptive Statistics and When They’re Used ○ Measures of Central Tendency (tells us what the sample as a whole, or on the average, is like ■ Mean - a set of scores is obtained by adding all the scores and dividing by the number of scores 1. Appropriate indicator of central tendency only when scores are measured on an interval or ratio scale, because the actual values of the numbers are used in calculating the statistic ■ Median - the score that divides the group in half (with 50% scoring below and 50% scoring above the median_ 1. Abbreviated as Mdn in scientific reports 2. Appropriate when scores are on an ordinal scale because it takes into account only the rank order of the scores 3. Also useful with interval and ratio scale variables ■ Mode - the most frequent score 1. The only appropriate measure if a nominal scale is used 2. Does not use the actual values on the scale, but simply indicates the most frequently occurring value■ *the median or mode can be a better indicator of central tendency than the mean if a few unusual scores bias the mean ○ Measures of Spread (Dispersion) ■ Range - the difference between the highest score and the lowest score ■ Quartiles - each of four equal groups into which a population can be divided according to the distribution of values of a particular variable 1. Quartile 1 (Q1) = 25th percentile ~ includes 25% of the data 2. Quartile 2 (Q2) = 50th percentile ~ includes 50% of the data; median 3. Quartile 3 (Q3) = 75th percentile ~ includes 75% of the data ■ Variance - a measure of the variability of scores about a mean; the mean of the sum of squared deviations of scores from the group mean 1. ■ Standard Deviation - indicates the average deviation of scores from the mean1. Symbolized as SD in scientific reports 2. Derived by first calculating the variance(s )2 3. SD is small when most people have similar scores close to the mean 4. SD is larger as more people have scores that lie farther from the mean value 5. SD = square root of variance 6. Usually uses the actual value of the scores 7. Appropriate for only interval and ratio scale variables 8. Quantitative vs. Qualitative Approaches ○ Quantitative ■ Tends to focus on specific behaviors that can be easily quantified (counted) ■ Researchers use large samples ■ Results are based on statistical analysis of data ■ Ex. develop questionnaire for a sample of teenagers 1. Ask the number of hours they work, the type of work they do, their levels of stress, their school grades, and their use of drugs 2. Assign numerical values to the responses 3. Use statistical analysis of the data 4. Results would focus on such things as the percentage of teenagers who work and the way this percentage varies by age ○ Qualitative ■ Focuses on people behaving in natural settings and describing their world in their own words ■ Researchers use small samples or a small setting ■ Results are based on the investigator’s interpretations ■ Ex. you want to describe behavior1. Conduct a series of focus groups (groups of 8-10 teenagers) 2. Engage groups in discussion about their perceptions and experiences with the world of work 3. Ask them to tell you about the topic in their own words and their own ways of thinking about the world 4. Record the discussion with a video or audio player or have an observer take detailed notes 5. A qualitative description of the findings would focus on the themes that emerge from the discussions and the manner in which the teenagers conceptualized the issues 6. Qualitative because it is expressed in nonnumerical terms using language and images 9. Types of Observation ○ Naturalistic ■ Sometimes called field work or field observation ■ Researcher makes observations of individuals in their natural environments (the field) ■ Researchers do not attempt to influence what occurs in the setting ■ Goal of naturalistic observation: provide a complete and accurate picture of what occurred in the setting, rather to test hypotheses formed prior to study ■ Researchers must keep detailed field notes on everything that occurs 1. First goal is to describe the setting, events, and persons observed 2. Second goal is to describe the settings, events, and persons observed a. Interpret what occurredb. Generate hypotheses to help explain the data and make them understandable 3. Specific examples of events that occurred during observation are used to support the researcher’s interpretations a. A good report will support the analysis by using multiple confirmations (ex. Similar events may occur several times, similar information may be reported by two or more people, and several different events occur that all support the same conclusion) 4. Data in naturalistic observation studies are typically qualitative ~ they describe the observations themselves rather than statistical summaries (quantitative) a. Can also be quantitative i. Ex. income, family size, education levels, age, gender ii. Can be reported and interpreted along with qualitative data ■ Limits 1. Most useful when investigating complex social settings both to understand the setting and to develop theories based on the observations -> less useful for studying well-defined hypotheses under precisely specified conditions or phenomena that are not directly observable by a researcher in a natural setting (ex. Color perception, mood, response time on a cognitive task) 2. Researcher is placed in an unfamiliar setting for extended periods3. There is an ever-changing pattern of events -> not all events are important, but every event must be recorded a. Researchers must adjust to new events 4. There are many field notes to sort through in order to form the analysis a. Researcher must repeatedly sort though the data to develop hypotheses to explain the data and then make sure all the data are consistent with the hypotheses ○ Systematic ■ The careful observation of one or more specific behaviors in a particular setting ■ Researcher is interested in only a few very specific behaviors ■ Observations are quantifiable ■ Researcher frequently has developed prior hypotheses about the behaviors ■ Can be applied in naturalistic and laboratory settings ■ Coding System 1. A set of rules used to categorize observations 2. Ex. Bakeman and Brownlee ~ interested in the social behavior of young children a. Videotaped three-year-olds for 100 minutes b. Coded each child’s behavior every 15 seconds using the following coding system: i. Unoccupied ii. Solitary play iii. Together iv. Parallel play v. Group play ■ Methodological Issues 1. Equipmenta. You can use paper and pencil measures; however, it is becoming more common to use video and audio recording equipment -> provides a permanent record of the behavior that can be coded later 2. Reactivity a. The possibility that the presence of the observer will affect people’s behaviors b. Can be reduced by concealed observation c. Using small cameras and microphones can make the observation unobtrusive d. Can be reduced by allowing time for people to become used to the observer and equipment 3. Reliability a. The degree to which a measurement reflects a true score rather than measurement error b. Reliable measures are stable, consistent, and precise c. When conducting systematic observation, two or more raters are usually used to code behavior i. High agreement among raters = reliability 4. Sampling a. Samples of behavior are taken over an extended period of time -> more accurate and useful than data from a single, short observation 10. Surveys ○ Why conduct surveys? ■ Important ~ gives real data rather than intuition and anecdotes1. Constantly being conducted through newspapers, news broadcasts, and the Internet 2. Common method of studying behavior 3. Can be important for sellers to collect data from buyers to assess and improve product quality and customer satisfaction 4. Can be important for making public policy decisions by lawmakers and public agencies ■ Many important variables (attitudes, current emotional states, self-reports of behavior, etc.) are most easily studied using questionnaires or interviews ■ Get a snapshot of how people think at a given time ■ To get a snapshot of how people behave at a given point in time ■ To study relationships among variables ■ To study ways that attitudes and behaviors change over time ■ Issues: 1. Response set a. A tendency to respond to all questions from a particular perspective rather than to provide answers that are directly related to the questions i. Can affect the usefulness of data obtained from self reports ii. Ex. always answering “strongly agree” 2. Social Desirability a. “Faking good” b. A response set that leads the individual to answer in the most socially acceptable way c. Can lead a person to underreport undesirable behavior (ex. Alcohol or drug use) andoverreport positive behaviors (ex. Amount of exercise) 3. When there is a center (neutral) people tend to choose that ■ Constructing Questions by Defining the Research Objectives 1. The first thing the researcher must do is explicitly determine the research objectives: what is it that he or she wishes to know? 2. Survey questions must be tied to the research questions that are being addressed 3. Usually requires the researcher to decide on the type of questions to ask 4. Three general types of survey questions a. Attitudes and beliefs i. Focus on the way that people evaluate and think about issues b. Facts and demographics i. Factual questions ask people to indicate things they know about themselves and their situation ii. Asking some demographic information is necessary to adequately describe your sample; thus, questions about age, gender, and ethnicity are typically asked. iii. It is unwise and unethical to ask people to respond to questions if you have no real reason to use the information c. Behaviors i. Focus on past behaviors or intended future behaviors 5. Question Wordinga. Simplicity i. Questions asked should be relatively simple ii. People should be able to easily understand and respond iii. Avoid jargon and technical terms 1. If needed, then provide a brief description b. Double-barreled questions i. Avoid questions that ask two things at once ii. Difficult to answer because it taps two potentially very different attitudes iii. Ex. Should senior citizens be given more money for recreation and food assistance programs? 6. Loaded Questions a. Written to lead people to respond in one way b. Ex. Do you favor eliminating the wasteful excesses in the public system budget? Vs Do you favor reducing the public school budget? c. Questions that include emotionally charged words such as rape, waste, immoral, ungodly, or dangerous influence the way that people respond and thus lead to biased conclusions d. Neutral, behavior-based terminology is preferable 7. Negative wording a. Avoid phrasing questions with negatives b. Ex. Do you feel that the city should not approve the proposed women’s shelter? i. Agreement with this question = disagreement with the proposalii. Phrasing can be confusing iii. Should be: Do you believe that the city should approve the proposed women’s shelter? 8. “Yea-saying” and “nay-saying” a. A tendency to employ a response set to agree or disagree with all the questions b. Respondent may simply be agreeing with everything you say c. Can be avoided by wording the questions so that consistent agreement is unlikely ■ Responses to Questions 1. Closed-ended questions a. Limited number of response alternatives are given b. More structured approach c. Easier to code and the response alternatives are the same for everyone d. More likely to be used when the dimensions of the variables are well-defined 2. Open-ended questions a. Respondents are free to answer in any way they like b. Require time to categorize and code the responses c. More costly to conduct and more difficult to interpret d. Sometimes a respondent’s response cannot be categorized at all because the response does not make sense or the person could not think of an answer e. Can yield valuable insights into what people are thinkingf. Most useful when the researcher needs to know what people are thinking and how they naturally view their world 3. The two approaches can sometimes lead to different conclusions a. Ex. survey asking about preparing children for life i. When “to think for themselves” was one alternative in a closed ended list -> 62% chose this ii. Only 5% chose this when the open-ended format was used iii. This shows that a good understanding of the topic is needed when having closed-ended questions ■ Administering Surveys 1. Questionnaires a. Questions are presented in written format and the respondents write their answers b. Pros: i. Generally less costly than interviews ii. Respondent can be completely anonymous c. Cons: i. Require that respondents be able to read and understand the questions ii. Can be boring to sit by themselves reading the questions and providing answers -> problem of motivation may arise d. Can be administered in person to groups or individuals, through the mail, on the internet, and with other technologies2. Personal Administration to Groups or Individuals a. Researchers are often able to distribute questionnaires to groups of individuals b. Ex. college class, parents attending a school meeting, people attending a new employee orientation c. Advantages: i. you have a captive audience that is likely to complete the questionnaire once they start it ii. Researcher is present to answer any questions 3. Mail Surveys a. Surveys can be mailed to individuals at a home or business address b. Inexpensive way of contacting the people who were selected for the sample c. Drawbacks: i. low response rates ii. Questionnaire can easily be placed aside and forgotten iii. Something may distract them from completing the survey iv. May become bored and throw the form away v. No one is present to help the person if they become confused or have a question about something 4. Online a. Easy to design a questionnaire for online administration using one of several online survey software servicesb. Both open- and close-ended questions can be included c. Responses are available for the researcher immediately after the questionnaire is completed d. How do people get the link? i. Major polling organizations have databases of people interested in participating in surveys ii. Mailing lists can be purchased iii. Online special interest groups for people with a particular illness or of a particular age may allow the researcher to post a recruitment message e. Concern: will the results be similar to what might be found using traditional data collection methods? f. Problems: i. response rates 1. Online surveys had an 11% lower response rate than other strategies 2. Can directly impact the validity of the data generated by such a survey ii. Ambiguity of the characteristics of the individuals providing information 1. Researchers usually state that persons 18 years of age or older are eligible, but this isn’t controlled online 2. People may misrepresent their age, gender, or ethnicity■ Interviews 1. People are often more likely to agree to answer questions for a real person than to answer a mailed questionnaire 2. Good interviewers become quite skilled in convincing people to participate -> higher response rates 3. Interviewer and respondent develop a rapport that helps motivate the person to answer all the questions and complete the survey a. People are more likely to leave questions unanswered on a written questionnaire than in an interview 4. Interviewer can clarify any problems the person may have in understanding the questions 5. Interviewer can ask follow-up questions if needed 6. Interviewer bias - all of the biases that can arise from the fact that the interviewer is a unique human being interacting with another human being -> interviewer could subtly bias the respondent’s answers by inadvertently showing approval or disapproval of certain answers a. Interviewer characteristics such as race, sex, or age can influence responses, especially when asking about sensitive topics b. Interviewers may have expectations that could lead them to “see what they are looking for” in the respondents’ answers -> can bias the interpretations of responses or lead them to prove further for an answer from certain respondents but not from others 7. Careful screening and training of interviewers help to limit biases8. Face-to-Face Interviews a. Face-to-face interviews - require that the interviewer and respondent meet to conduct the interview b. Usually the interviewer travels to the person’s home or office, although sometimes the respondent goes to the interviewer’s office c. Tend to be quite expensive and time-consuming d. Most likely to be used when the sample size is small and there are clear benefits to a face-to-face interaction 9. Telephone Interviews a. Almost all interviews for large-scale surveys are done via telephone b. Telephone interviews - less expensive than face-to-face interviews, and they allow data to be collected relatively quickly became many interviewers can work on the same survey at once c. Computerized telephone survey techniques lower the cost of telephone surveys by reducing labor and data analysis costs d. Computer-assisted telephone interview (CATI) - interviewer’s questions are prompted on the computer screen, and the data are entered directly into the computer for analysis 10. Focus Group Interviews a. Often used in industry b. Focus group - an interview with a group of about 6 to 10 individuals brought together for a period of usually 2-3 hoursc. Group members are often selected because they have a particular knowledge or interest in the topic d. Virtually any topic can be explored in a focus group e. Participant usually receive some sort of monetary or gift incentive f. Questions tend to be open-ended and are asked of the whole group g. Advantage: group interaction is possible -> people can respond to one another, and one comment can trigger a variety of responses h. Interviewer must be skilled in working with groups both to facilitate communication and to deal with problems that may arise, such as one or two persons trying to dominate the discussion or hostility between group members i. Discussion is usually recorded and may be transcribed i. Tapes and transcripts are then analyzed to find themes and areas of group consensus and disagreement ii. Sometimes analyzed with a computer to search for certain words or phrases j. Usually prefer to conduct two or three discussion groups on a given topic to make sure that the information gathered is not unique to one group of people 10. Case Study Research○ An observational method that provides a description of an individual or setting ○ Often overlaps with a naturalistic observation, but does not have to be naturalistic ○ Can be a description of a patient by a clinical psychologist or a historical account of an event such as a model school that failed ○ Psychobiography ■ A type of case study in which a researcher applies psychological theory to explain the life of an individual, usually an important historical figure ○ Use techniques such as library research and telephone interview with persons familiar with the case but no direct observation at all ○ May present the individual’s history, symptoms, characteristic behaviors, reactions to situations, or responses to treatment ○ Typically done when an individual possesses a particularly rare, unusual, or noteworthy condition ○ Valuable in informing us of conditions that are rare or unusual and thus providing unique data about some psychological phenomenon, such as memory, language, or social exchange ○ Insights gained through a case study may also lead to the development of hypotheses that can be tested using other methods 11. Probability vs. Nonprobability Research ○ Probability sampling - each member of the population has a specifiable probability of being chosen ■ Required when you want to make precise statements about a specific population on the basis of the results of your survey ○ Nonprobability sampling - the probability of any particular member of the population being chose is unknown12. Sampling Techniques ○ Probability Sampling ■ Simple Random Sampling 1. Simple random sampling - every member of the population has an equal probability of being selected for the sample a. Ex. sample students from your school i. From a list of every student in the, students are randomly chosen to form a sample 2. Random sample - every possible sample that could be selected has a predetermined probability of being selected a. Ex. conducting a telephone interview i. A computer randomly generates a list of telephone numbers with the dialing prefixes used for residences in the city or area being studied ii. Random sample of households rather than individuals ■ Stratified Random Sampling 1. Stratified random sampling - the population is divided into subgroups(strata), and random sampling techniques are then used to select sample members from each stratum 2. Grouping should be relevant to the study a. Ex. survey of sexual attitudes might stratify based on age, gender, and amount of education because these factors are related to sexual attitudes i. Stratification based on height or hair color would be ridiculous for this survey3. Has built-in assurance that the sample will accurately reflect the numerical composition of the various subgroups a. Good because some subgroups represent very small percentages of the population b. Ex. if African Americans make up 5% of a a city of 100,000, a simple random sample of 100 people might not include and African Americans; a stratified random sample would include five African Americans chosen randomly from the population 4. When it is important to represent a small group within a population, researchers will “oversample” that group to ensure that a representative sample of the group is surveyed -> a large enough sample must be obtained to make inferences about the population ■ Cluster Sampling 1. Cluster sampling - researchers identify “clusters” of individuals and then sample from these clusters 2. Ex. conduct survey of students using cluster sampling by identifying all classes being taught a. The classes are clusters of students b. You can then randomly sample from this list of classes and have all members of the chosen classes complete your survey 3. Often requires a series of samples from larger to smaller clusters a. Ex. a researcher interested in studying country health care agencies might first randomly determine a number of states to sample and then randomly sample counties from each state chosen4. Advantage: researcher does not have to sample from lists of individuals to obtain a truly random sample of individuals ○ Nonprobability Sampling ■ The probability of being selected is not known ■ A population may be defined, but little effort is expended to ensure that the sample accurately represents the population ■ Cheap and convenient ■ Three types: haphazard sampling, purposive sampling, and quota sampling ■ Haphazard Sampling 1. Haphazard sampling - “convenience sampling”; selecting subjects in a haphazard manner, usually on the basis of availability, and not with regard to having a representative sample of the population 2. Ex. ask people who sit around you in your classes 3. Sample contains many biases 4. Results may not generalize to intended population ■ Purposive Sampling 1. Purposive sampling - to obtain a sample of people who meet some predetermined criterion 2. Ex. an age group ■ Quota Sampling 1. Quota sampling - collect specific proportions of data representative of percentages of groups within population, then use haphazard techniques 2. No restrictions placed on how individuals in the various subgroups are chosen 13. Null Hypothesis and Alternative Hypothesis (Research Question) ○ Null hypothesis(H0) = the means are equal; the observed difference is due to random error ■ States that the independent variable had no effect■ If we can determine that the null hypothesis is incorrect, then we accept the research hypothesis as correct ■ Reject when we find a very low probability that the obtained results could be due to random error ■ Used because it is a precise statement - the population means are exactly equal -> permits us to know precisely the probability of obtaining our results if the null hypothesis is correct ○ Research hypothesis = the population means are not equal ■ States that the independent variable did have an effect ■ Acceptance of the research hypothesis means that the independent variable had an effect on the dependent variable ■ Can infer that it is correct only by rejecting the null hypothesis ○ First, check the p-value ○ If p is greater than or equal to .05, accept the null ○ If p is less than .05, reject the null ○ Accepting the null means there are no differences 14. Type I and Type II Errors ○ Type I Errors ■ Type I error - made when we reject the null hypothesis but the null hypothesis is actually true ■ Occur when, simply by chance, we obtain a large value of t or F 1. When we obtain such a large value by chance, we incorrectly decide that the independent variable had an effect ■ Probability of making a Type I error is determined by the choice of significance level (alpha) 1. If the null hypothesis is rejected, there are chances out of 100 that the decision is wrong■ Probability of making a Type I error can be changed by either decreasing or increasing the significance level ○ Type II Errors ■ Type II error - occurs when the null hypothesis is accepted although in the population the research hypothesis is true ■ The population means are not equal, but the results of the experiment do not lead to a decision to reject the null hypothesis ■ Probability of a Type II error(beta) is related to three factors: 1. significance(alpha) level a. Choose a significance level that makes it more difficult to reject the null hypothesis 2. Sample size a. True differences are more likely to be detected if the sample size is large 3. Effect size a. Large effect size = unlikely chance of Type II error

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