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- I'm needing help with part 1 through 3, please The data of Sugar Water and Plain Water: mean # of drops variance degrees of freedom t stat t crit (from the table) plain water 25.3 17.221 38 -4.01 2.0261 sugar water 21.3 21.256 1. Make a statement about t stat in relation to t crit. And what is the p-value? 2. Is there a statistically significant difference between the mean values (mean # of drops) of the sugar and plain water? Give your "yes" or "no" answer and the supporting evidence. 3. Hypothesis: The surface tension of plain water is higher than the surface tension of sugar water. Do these results support or refute the hypothesis about the effect of dissolving salt in water on surface tension?One basic purpose of experimental design is to reduce the number of participants needed O to control variance to keep the alpha level below.05 O to observe contingenciesThe 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.
- When a correlation coefficient is statistically significant, what doyou conclude about the two variables? What do the results meanwith regard to cause and effect?can you help me answer these 1-4 questions? please thank you! 1. how do you compare product rule from the sum rule of probabilities? 2. What is the importance of sample size and choice of test organism in studies involving probabilities? 3. Differentiate mean, variance, and standard deviation. 4. What does a relatively small standard deviation indicate?What is the advantage of using affine gap scores?
- With an alpha of 0.05, what fraction of results would you expect to give you a false positive? [evidence of significant difference when the distributions actually don't differ significantly] O one time out of five hundred O one time out of one hundred Oone time out of ten O one time out of five one time out of twentyWith respect to the concerted model, what is the L value? What is the c value?page - Columbus State Uni X content/2622738/viewContent/50155728/View + Calculating the Value of Chi-Square Once you've defined the null hypothesis (and know what you're testing!), you can finally calculate the chi-square value based on your observed data and the expected distribution. There are many statistical software packages and free web-based applications that will automate the calculation for you, but it's important to understand the calculation to understand the meaning of the calculated value. Here, we'll walk through it using a calculation table. This is Mendel's historic data for the F2 generation of monohybrid cross for flower color. Recall that he expected to see in the F2 generation a ratio of 3 purple : 1 white. Chi-square calculation for data from a monohybrid cross with an expected 3 purple : 1 white ratio. Outcomes Observed (0) Expected (E) O-E (0-E)2 (O-E)²/E Purple White Totals 705 224 929 X²= The first step is to calculate the expected (E) values for purple and…
- If you perform a Chi-Squared analysis and determine that your result is greater than the critical value, what would you do? a. Reject H0, accept HA b. Accept H0 c. neitherCan you explain how to get the percentage in this problem? Thank you! V. The comparison of the class blood group with the national average distribution is given as follows like: O+ = 19 AB+ = 5 A+ = 7 B+ = 2 so the table for national average distribution is: 1.Blood type Percentage National Average Distribution A+ 21.21% 24.64% B+ 6.06% 23.84% AB+ 15.15% 46% O+ 57.57% 46.94%1) You compare the height and weight of 5 adult women. You get the following results:height 60 67 62 70 66weight 119 143 131 155 136(a) Construct a scatter plot of height (x) vs. weight (y)(b) Calculate the following (show your work for SScp):SSx SSy SScp ̄x ̄y(c) Calculate the correlation coefficient (r)2) Use the information from problem 1. Perform a complete test of the hypothesis that the populationcorrelation coefficient (ρ) is 0. Show all steps (note - obviously this should be a one sided test! Make sure youknow why!).3) Now let's assume you wanted to predict weights from heights. In other words, now let's use the same datafrom problem (1) and do a regression instead.(a) Calculate b0 and b1.(b) Carefully draw your least square regression line on the plot you made in 1(a). (Don't just “sketch”,be a little careful).4) (a) Now do a significance test of H0: β1 = 0. Show all your calculations (including your residualcalculations). Again, note that this should be a one sided test…
