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the differences between the measured values and the predicted values are too large to allow us to attribute them to chance |
the differences between the measured values and the predicted values are not significant and can be attributed to chance |
the measured values are too small to allow a prediction to be made |
there should be no numerical difference between the measured and the predicted values |
None of the other answers are correct. |
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- I am testing the prediction that spiders with colors that match a flower (cryptic coloration) will have greater success hunting bees visiting that flower. I set up two treatments for spiders: those matching their flower and those not matching their flower. I measure how long it takes each of them to catch a bee. What kind of statistical test would be best for testing my prediction? Chi-square ●ANOVA RegressionWhen a correlational study demonstrates a relationship between two variables, it allows researchers to use knowledge about one variable to ______________ the second variable. Describe how the third-variable problem and the directionality problem limit the interpretation of results from correlational research designs and support that a correlational study may establish that two variables are related, it does not mean that there must be a direct relationship between the two variables.The following statements are either true or false. Indicate true or false and justify your answer briefly. An unbiased estimator is said to be consistent if the difference between the estimator and the population parameter grows smaller as the sample size grows larger. An unbiased estimator is a sample statistic whose expected value equals the population parameter. Knowing that an estimator is unbiased neither assures us that its expected value equals the population parameter, nor does it tell us how close the estimator is to the population parameter. A specific confidence interval obtained from sample data will always correctly estimate the population parameter.
- The confidence interval is reported as follows: Lower 95% CI < p < Upper 95% CI For this question you will be calculating the confidence interval but only reporting the Upper 95% CI using the Agresti-Coull Method. ( (you'll need to know the whole 95% CI for a future question) Do NOT use calculations from previous questions, this is a new scenario. In the Invisible Gorilla Experiment, 24 students were watching the video, only 7 noticed the gorilla. Calculate the 95% CI using the Agresti-Coull method, but only report the Upper 95% CI. Report your answer to 3 decimals.what is the Expectation and outcome of results, Logical interpretation of the dataand any errors?The following statements about the chi square test are correct. (Read each statement carefully. Select all of the statements below that are true (that you agree with). Leave any statements that are false (that you do not agree with) un- selected.) The null hypothesis infers that chance alone cannot account for the differences between observed and expected data. The null hypothesis infers that observed values are close enough to expected values. The lower the overall chi square value, the more likely the null hypothesis will be accepted. The higher the probability range associated with the overall chi square value, the more likely the null hypothesis will be rejected.
- 1) Chi-square analysis generates a p value, an important indicator of statistical support for a hypothetical outcome. If a p value = 0.05 > p > 0.01, the tested hypothesis fails to be falsified. Agree/Disagree? Answer with explanation here:Person 1 Person 2 Person 3 Person 4 Person 5 Person 6 i Y; (0) 3000 2500 3000 1500 4000 5000 Y; (1) 4000 3000 2500 4000 5500 6000 D₁ 1 0 1 0 1 0 (a) Explain the "fundamental problem of causal inference." Using all of the potential outcomes in the table, what is the average treatment effect?Which of the following are variable terms in the discrete-time logistic model? ΔN Δt rmax,d t Nt K None of these
- I just want someone to look over my answers to make sure I am calculating correctly. I am using the Hardy-Weinberg Equlibrium to figure out the answers to the questions. Thank you,Dr. Vanier’s daughter Lexy thinks that the snacking habit alone does not cause weight loss. She believes that one needs to combine no snacking with the elimination of carbohydrates in their meals. Please explain how Dr. Vanier may test this hypothesis by describing the research design. Specify the independent variable(s), dependent variable(s), and the name of the design. Finally, describe what she needs to find (i.e., what type of effect and what it looks like) in the experiment to support her hypothesis. ( name the IV(s); 1name the DV(s); name the design; then explain the effect that will support the hypothesis)In an experiment, the control group is used to: a Change the variable b Provide a baseline for comparison with the test group c add additional non-dependent variables d demonstrate correlation rather than causation e generate hypotheses