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• For each of the following examples, explain whether the researcher has made a correct decision or has made a Type 1 or Type 2 error. Explain why. 1. Dr. G rejects the null hypothesis although the... independent variable had no effect. 2. Dr. R rejects the null hypothesis when it is false. 3. Although the independent variable had an effect, Dr. E does not reject the null hypothesis Your Answer: 1. Type I error is made when we reject the null hypothesis, but the null hypothesis is actually true. Our decision is that the population means are not equal when they actually are equal- rejecting something that is true. 2. This would be a valid choice as Dr. R is rejecting a hypothesis that is false. 3. A 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 – failing to reject something that is false • Question Points: 16.0 / 16.0 • 2 Explain the value of reversal designs (ABA designs) in single-case research. Your Answer: According to Privitera (2020), reversal designs are usually conducted in applied areas of research in order to investigate solutions that can be beneficial to either individuals or our society. One advantage is that the design can be used to apply treatments that benefit participants. In a reversal design (ABA design), a single participant is observed prior to (A), during (B), and after (A) a manipulation or treatment (p. 257-258) A (baseline phase) --> B (treatment phase) --> A (baseline phase) • Question Points: 10.0 / 16.0 • 3 Explain how a one-way analysis of variance works. How do you use between- and within-group variability? Your Answer: One-way analysis of variance (one-way ANOVA) looks at the differences between the mean of 2 or more samples. Between-group variability looks at the variations caused by differences between different groups. Within-groups variability looks at variations caused by differences within each individual group, differences not caused by the independent variable. • Question Points: 10.0 / 16.0 • 4 After watching nursery-school children, Ken Garoo wants to test the hypothesis that some toys are more fun to play with than others. He decides to compare “fun” toys (blocks) with “unfun” toys (stuffed animals). He also wishes to see if there is a sex difference, as well, so sex is added as an independent variable. A) What kind of design is needed? B) Diagram it out. C) Assuming 20 subjects are needed per cell, how many subjects are needed for this study? Your Answer: a) The type of design would be a 2x2 factorial design as it will test the factors within one sample. b) Males Females Fun Toys (blocks) 20 20 Un-Fun Toys (stuffed animals) 20 20 c) 80 subjects would be needed if there are 20 subjects per cell as visualized above (20x4 = 80) • Question Points: 16.0 / 16.0 • 5 Bill Board is “lording” his SAT score over his friend, Rhoda Dendron, who took the ACT. “You only got a 25 in math,” he chortled, “while I got a 300 in math.” Given that the SAT has a μ of 500 and a σ of 100, and the ACT has a μ of 20 and a σ of 5, what is wrong with Bill’s logic (give the answer in both z scores and percentile ranks). Your Answer: Bill is incorrect to “lord” his SAT score because the SAT and the ACT use different scoring methods. z-score: z = x – μ / SD Bill’s z-score is 300-500 / 100 = -2 Rhoda’s z-score is 25-20 / 5 = 1 Percentiles: SAT Math: 300/800 = 37.5% ACT Math: 25/36 = 69% (36 is the highest you can score in ACT Math) Bill’s z-score of -2 puts him below Rhoda’s z-score of 1 as she is closer to average than he is. • Question Points: 14.0 / 16.0 • 6 Describe a two-matched groups design. How is the matching done? Your Answer: According to Privitera (2020), matched-sample designs are within-subject designs where participants are matched either experimentally or naturally based on pre-existing traits that they both share (p. 317) A two-matched group design uses a pair of subjects with similar variables (for example twins). Matching is primarily done by finding a variable that can impact or have an effect on the dependent variable. The participants are then randomly assigned one member of each pair to the experimental condition and the other individual to the controlled condition. • Question Points: 10.0 / 16.0 • 7 Chuck Wagon is very excited about the within-subjects approach. “Now I’ll never need to run large numbers of subjects again,” he says. However, Chuck has forgotten that within-subjects designs may be a) useless, b) impossible, c) confounded by order effects, or d) impractical when excessive subject time spent in an experiment makes data inaccurate. Give an example of each of these four objections. Your Answer: 1. A within-subjects design would be deemed useless if for example an individual is asked to learn the same list of words using different strategies, 2. An example of an impossible within-subjects design is a study of surgery vs. drug treatment for a disease; subjects generally would receive one or the other treatment, not both. 3. Order effects can be confounding variables because they can cause changes in the dependent variable from one treatment condition to the next that are not due to the treatment alone. For example, if a researcher is looking to measure spelling comprehension in three separate situations, the participant's score may improve on each test administration, however, the participants' performance may also get worse on each administration due to becoming fatigued. 4. If a study takes an excessive amount of time, the participants may become restless or fatigued which may lead them to drop out of the study. Additionally, if a participant becomes fatigued due to the excessiveness of the study, the study’s hypotheses may turn out false due to the participant’s unwillingness to focus on the conditions presented in the study, thus proving inaccurate data. • Question Points: 16.0 / 16.0 • 8 A researcher has studied subjects’ ability to learn to translate words into Morse code. He has experimented with two treatment conditions: in one condition, the subjects are given massed practice; they spend 8 full hours on the task. In the other condition, subjects are given distributed practice; they also spend 8 hours, but their practice is spread over four days, practicing 2 hours at a time. After the practice, all subjects are given a test message to encode; the dependent variable is the number of errors made. The researcher has matched the subjects on intelligence. The results are in the following table. Decide which statistical test would be appropriate, carry out the test, and evaluate the outcome. Assume a significance level of .05 and that the direction of the outcome has not been predicted. Your Answer: The statistical test used would be a paired t-test (parametric) where t = -1.58 and the value for p = 0.19. Since the significant level is 0.05, the results would not be significant • Question Points: 16.0 / 16.0 • 9 Explain the pros and cons of longitudinal, cross-sectional, and sequential designs. Your Answer: Longitudinal design is a research design which uses observation to study changes across the lifespan of a participant over different points in time while measuring the same dependent variable each time a. Pro: Provides developmental analysis, changes in the participant's behavior can be evaluated over time, researchers can gather a large amount of data over a period of time. Variable patterns can be seen throughout the study. b. Con: Can be expensive, participant attrition, there are many threats to internal validity, can take a long time (Privitera, 2020) Cross-sectional design groups participants by their age and the participants' characteristics are measured in each age group a. Pro: Participants can be observed over time in each cohort which can eliminate numerous threats to internal validity when it comes to observing participants over time. Attrition, test effect, and regression towards the mean are usually also not a concern when participants are observed only one time. It can also be cost-effective. b. Con: Cohort effect and generation effect which is a threat to internal validity as participants in different cohorts or age groups misperceive or otherwise explain an observed result, and may contain biases (Privitera, 2020). Sequential design is a combination of longitudinal and cross-sectional design by observing different cohorts of individuals over time at overlapping times (Privitera, 2020). a. Pro: Can be a bit more accurate in measuring observed changes than cross-sectional and longitudinal design and researchers can test a single variable over the course of the study. Sequential designs are also less time consuming and can measure the generation effect. b. Con: Cannot make accurate causal analysis and can be costly, • Question Points: 16.0 / 16.0 • 10 Define the term quasi-experiment and discuss the pros and cons of this research method. Your Answer: Quasi-experimental research design is structured similarly to an experiment except that the study lacks random assignment, includes a preexisting factor, includes variables that are not manipulated, and doesn’t have a control group. A quasi-experimental design lets researchers study independent variables that are not assigned in random order. Quasi-experiments are typically used to study the relationship between cause and effect where it is nearly impossible, unethical, or impractical to use randomization (Privitera, 2020) Pro: Uses applied research when experiments are not possible, easily set up, there are less ethical considerations than an experimental design, often offers higher external validity Con: There are threats to internal validity, statistical analysis can be sometimes difficult, ethical concerns can still arise, there can be issues with replicability • Question Points: 16.0 / 16.0 [Show More]

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