Use the data given in the table below to compute the probability that a randomly chosen voter from the survey will satisfy the following. Round to the nearest hundredt ho uoter i
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.Recall that the general form of a logistic equation for a population is given by P(t)=c1+aebt , such that the initial population at time t=0 is P(0)=P0. Show algebraically that cP(t)P(t)=cP0P0ebt .A student releases a ball on a ramp, letting it roll down the ramp. Using a meter stick, she measureshow far it rolls in half of a second. She then repeats this process, increasing the time she allows the ball to rollwith each trial. The data is given below:Time (s) Distance (cm)0.0 00.5 51.0 251.5 552.0 1002.5 1553.0 2253.5 3054.0 4004.5 5055.0 6251. What is the independent variable for the experiment?2. What is the dependent variable for the experiment?
- A dietitian wishes to see if a person’s cholesterol level will change if the diet is supplemented by a certain mineral. Six randomly selected subjects were pretested, and then they took the mineral supplement for a 6-week period. The results are shown in the table. (Cholesterol level is measured in milligrams per deciliter.) Can it be concluded that the cholesterol level has been changed at α = 0.10? Assume the variable is approximately normally distributed. Subject 1 2 3 4 5 6 Before (x1) 210 235 208 190 172 244 After (x2) 190 170 210 188 173 288 Required Steps: Step 1: Label all given information. Step 2:State the null and alternative hypothesis and identify the claim. Step 3:Verify that the conditions are met to perform the test. Step 4:Sketch the normal distribution and find the critical regions. Step 5:Compute the test statistic. Step 6:Make a decision Step 7:Summarize the results.X” denote the number of children ever born to a woman, and let “Y” denote years ofeducation for the woman. A simple model relating fertility to years of education is X = β0 + β1Y + u where u is the unobserved error. (i) What kind of factors are contained in u? Are these likely to be correlated with level of education?What type of model is presented below – Model 3. What impact do d_y and d_rs have on the dependent variable d_m_p? Model 3: OLS, using observations 1980:2-1999:3 (T = 78) Dependent variable: d_m_p Coefficient Std. Error t-ratio p-value const 0.0113971 0.00130078 8.7617 <0.0001 *** d_y −0.0106911 0.100221 −0.1067 0.9153 d_rs 0.00151462 0.00110613 1.3693 0.1751 d_rl 0.000127744 0.00141954 0.0900 0.9285 d_p −0.354204 0.093535 −3.7869 0.0003 *** Mean dependent var 0.007578 S.D. dependent var 0.004753 Sum squared resid 0.001399 S.E. of regression 0.004378 R-squared 0.195607 Adjusted R-squared 0.151531 F(4, 73) 4.437922 P-value(F) 0.002885 Log-likelihood 315.5363 Akaike criterion −621.0725 Schwarz criterion −609.2890 Hannan-Quinn −616.3554 rho 0.485424 Durbin-Watson 1.001216
- you are testing ho: u=0 against ha=u not equal 0 based on an SRS of four observations from a normal population. what are the values of the t static are statistically signification at a=0.005 levels? (a) t>7.453 (b) t<-7.453 or t>7.453 (c) t<-5.598 or t >5.5981. An older memory study by Eysenck (1974) compared the recall of older participants under one of 5 levels of processing of the learned material. He demonstrated that when asked to perform a higher level of processing a list of words, participants showed better recall at a later time. Eysenck also compared Younger and Older participants on their recall abilities when instructed that they should simply memorize the material for later recall. The data on 10 participants in each group follow, where the DV is the number of items recalled. Younger 21 19 17 15 22 16 22 22 18 21 Older 10 19 14 5 10 11 14 15 11 11 a. Conduct the analysis of variance comparing the means of these two groups. Do this one by hand, including stating your hypotheses, Finding the critical F, and completing the summary table, so that you can compare your test statistic to your critical F. b. Then, interpret your results. 2. Another way to look at Eysenck's study is…. I’m interested in assessing whether someone’s resting heart rate (X) is related to how fast they are able to finish running a 5k race (5k is 3.1 miles) (Y). I gather data from a set of runners and want to see whether, at an alpha of 0.05, there is a significant relationship between resting heart rate and finish time. Use the data below to answer this question: Resting Heart Rate (measured in beats/min) Finish Time (measured in minutes) (Y) 54 30 65 33 60 35 60 32 75 35 70 36 80 45 60 36 55 29 55 27 60 30 Calculate the sum of squares for XY __________________________ What is the correlation coefficient? Is it strong or weak? Positive or negative? __________________________ What can we conclude? ______________________________________________________________________