Formulate research problems and hypotheses to test the effect between 2 variables (variable X and variable Y). The following presents quantitative data from the measurement results of variables X and Y from a number of individuals (sample) taken randomly from a certain
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- Resting heart rate varies among different people. Design an experiment and examine whether or not a particular variable (e.g. fitness level, smoking, activity, age, gender) has an effect on heart rate. Begin by making one or more observations. Then formulate a hypothesis that can be tested. Finally, design an experiment to test your hypothesis! You can use yourself and any person you can talk to including family and friends Observations: State one or more observations related to your scientific Observation(s): The Heart rate will change depending on activity Hypothesis: Generate a hypothesis and include a justification for your Hypothesis: Male that are active will have a higher hear rate than females Experiment: Describe your experiment below and state the independent and dependent variables you will be exploring. Explain any specific instructions, e.g. how it will be carried out, how any measurements are to be made, if needed, etc……Can movie rental revenue be predicted? A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteen movies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is ŷ=3.38+0.15x. Theater revenue, x (in millions of dollars) Rental revenue, y (in millions of dollars) 21.0 5.5 60.9 10.0 61.0 16.0 27.5 3.1 36.7 12.7 30.6 5.7 14.8 2.0 49.6 15.7 13.1 10.2 25.9 8.9 44.1 6.5 66.9 9.5 27.5 11.8 24.9 7.9 6.9 1.5 Send data to calculator Send data to Excel Rental revenue (in millions of dollars) 18- 16+ x 14 12 10+ x 50 60 70…When results are not statistically significant, why do you conclude that it is plausible that the two variables are independent rather than concluding that the variables are different independent?
- The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of fifteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation y = 40.86-0.45x. This line is shown in the scatter plot below. Mileage, x (in thousands) 29.7 27.8 26.8 24.2 21.1 23.0 24.3 15.4 37.7 23.6 34.4 27.8 23.5 20.9 259 Used selling price, y (in thousands of dollars) 27.4 29.4 31.2 30.1 31.7 31.7 27.2 34.2 23.4 28.2 26.3 26.5 33.7 30.6 267 Used selling price (in thousands of dollars) 40- 35+ 30- 25- 20 THIS 15 X 20 X X X 30 Mileagex (in thousands) X 35 40Fish of Lake Laengelmaevesi. An article by J. Puranen of the Department of Statistics, University of Helsinki, discussed a classic study on several variables of seven different species of fish caught in Lake Laengelmaevesi, Finland. On theWeissStats site, we present the data on weight (in grams) and length (in centimeters) from the nose to the beginning of the tail for four of the seven species. Perform the required parts for both the weight and length data. a. Obtain individual normal probability plots and the standard deviations of the samples. b. Perform a residual analysis. c. Use your results from parts (a) and (b) to decide whether conducting a one-way ANOVA test on the data is reasonable. If so, also do parts (d) and (e). d. Use a one-way ANOVA test to decide, at the 5% significance level, whether the data provide sufficient evidence to conclude that a difference exists among the means of the populations from which the samples were taken. e. Interpret your results from part (d)6) The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment II 3. 6. N= 12 10 G = 60 1 10 EX = 392 1 5. 6. M = 3 M = 4 M= 8 T= 12 T= 16 T= 32 SS = 8 SS = 12 SS = 16 a) Use an ANOVA with a = .05 to determine whether there are any significant differences among the three treatment means. b) Calculate n² to measure the effect size for this study. c) Write a sentence demonstrating how a research report would present the results of the hypothesis test and the measure of effect size. 3.
- A researcher was interested in how the effects of stress were different in people with our without military training. A equal number of participants were recruited that either had no military experience or had completed military experience. All participants were asked to give a speech without preparation while being judged by a panel of experts. Their heart rates were monitored during the speech and an average heart rate was calcuated for each participant. Which statistical test would be best to determine if there is a significant difference between groups? one-sample t-test dependent samples t-test independent samples t-test ANOVAIs the dependent variable is always dependent to the independent variable(s) of the study? Why?The authors of the paper "Statistical Methods for Assessing Agreement Between Two Methods of Clinical Measurement" compared two different instruments for measuring a subject's ability to breathe out air.† (This measurement is helpful in diagnosing various lung disorders.) The two instruments considered were a Wright peak flow meter and a mini-Wright peak flow meter. Seventeen subjects participated in the study, and for each subject air flow was measured once using the Wright meter and once using the mini-Wright meter. Subject 1 2 3 4 5 6 7 8 9 Mini- Wright Meter 512 430 520 428 500 600 364 380 658 Wright Meter + 494 395 516 434 476 557 413 442 650 Subject 10 11 12 13 14 15 16 17 Mini- Wright Meter 445 432 626 260 477 259 350 451 Wright Meter 433 417 656 267 478 178 423 427 (a) Suppose that the Wright meter is considered to provide a better measure of air flow, but the mini-Wright meter is easier to transport and to use. If the two types of meters produce different readings but there is…
- The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)5. (10) A recent Gallup Organization Poll asked male and female Americans whether they were pro or pro choice when it comes to abortion issues. The results of the survey are as follows: life Opinion Pro-Life Pro-Choice Gender Men 195 200 Women 240 250 Test whether an individual's opinion regarding abortion is independent of gender at the a = 0.025 level of significance.PETROGAS is testing new filters for its motorbikes. One brand of filter (Filter A) is placed in one motorbike, and the other brand (Filter B) is placed in the second motorbike. Random samples of air released from the motorbikes are taken at different times throughout the day. Pollutant concentrations are measured for both motorbikes at the same time. The following data attached represent the pollutant concentrations (in parts per million) for samples taken at 20 different times after passing through the filters. a. Test the hypothesis that the mean for the pollutant concentration for Filter B is greater than 30. Use the 1% level of significance. b. Construct a 95% confidence interval for the difference in mean pollutant concentration, where a difference is equal to the pollutant concentration passing through Filter A minus the passing through Filter B. c. Using the 5% significance level, determine whether there is evidence that mean for the pollutant concentration for Filter A…