In soccer, serious fouls result in a penalty kick with one kicker and one defending goalkeeper. The accompanying table summarizes results from 281 kicks during games among top teams in thetable, jump direction indicates which way the goalkeeper jumped, where the kick direction is from the perspective of the goalkeeper. Use a 0.05 significance level to test the claim that the direction ofthe kick is independent of the direction of the goalkeeper jump. Do the results support the theory that because the kicks are so fast, goalkeepers have no time to react, so the directions of their jumpsare independent of the directions of the kicks?Click the icon to view the penalty kick data.Determine the null and alternative hypothesesOA H Jump direction is independent of kick direction.H₁: Jump direction is dependent on kick direction.OB. H: Goalkeepers jump in the direction of the kickH, Goalkeepers do not jump in the direction of the kickOC. H: Goakeepers do not jump in the direction of the kickH₁: Goalkeepers jump in the direction of the kickOD. H Jump direction is dependent on kick direction.H, Jump direction is independent of kick directionCETTEDetermine the test statisticx²(Round to three decimal places as needed.)Determine the P-value of the test statisticP-value (Round to four decimal places as needed.)Do the results support the theory that because the kicks are so fast, goalkeepers have no time to react, so the directions of their jumps are independent of the directions of the kicks?There isthe theory thatevidence to warrant rejection of the claim that the direction of the kick is independent of the direction of the goalkeeper jump. The resultsbecause the kicks are so fast, goalkeepers have no time to react Pentalty Kick DataKick to LeftKick to CenterKick to RightPrintGoalkeeper JumpLeft Center Right5004337123240562Done-X

From given data we have Observed Frequencies Goalkeeper Jump Row variable Left(B1)…

Answered: In soccer, serious fouls result in a…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A random sample of single males and single females (ages 21 to 76) was obtained. The sample includes those currently separated, divorced, or widowed. The subjects were given a trait and asked to respond whether the trait was a deal-breaker in terms of maintaining the relationship. The results of the survey are provided in the table for the trait "stubborn". Is there a significant difference between males and females who consider the trait "stubborn" a relationship deal-breaker? Use the a = 0.05 level of significance. Click the icon to view the survey results. State the null and alternative hypotheses. Ho: PM PF %3D Survey Results H1: PM + PF Determine the size of each sample. Trait: Stubborn = 544 Males Females NE = 556 Yes 174 189 (Type integers or decimals. Do not round.) No 370 367 Determine the sample proportion of each gender that considers stubbornness to be a relationship deal-breaker. Print Done PM PF = (Round to three decimal places as needed.)
Consider a study that surveyed 50 people to rate how much they like their job. Ratings mean 1 for “hate my job”, 2 for “dislike my job”, 3 for “neutral”, 4 for “like my job” and 5 for “love my job”. This survey found that • 8 people hated their job• 14 people disliked their job • 15 people were neutral• 9 people liked their job, and • 4 people loved their job. (1) Write a description of the random variable describing this survey(2) Write a probability distribution describing the probability of the outcomes of this event. (3) What probability of people like their job?(4) Calculate the expected rating.
Company A claims that their product is more consistent than Company B. Data is collected and the results are: Company A: n=11, mean= 16.3, s=.41 Company B: n=10, mean= 16.56, s=.05
Which of the following is NOT CORRECT? A) The past purchase frequency (freqi) affects the purchase probability positively – i.e., customers with high past purchase frequency are more likely to purchase our product in the next year than those with low past purchase frequency. B) In general, customers are likely to buy our product because the baseline parameter is negative. C) High-income customers are more likely to purchase our product in the next year than low- income customers because the coefficient corresponding to the income variable (incomei) is positive. D) Although the number of flyers (nmaili) positively affects the purchase probability, it is not guaranteed that sending flyers to customers as many as possible maximizes profits.
I need the p value Thankyou so much
What is Ha? (H0 is the mean VIQ scores for the younger, middle-aged, and older subjects are all not different from each other) (Note: 1= 5-25 Years, 2= 26-59 Years, 3= 60-92 Years) Multiple Choices: 1. H0 is not true 2. The mean VIQ scores for the younger, middle-aged, and older subjects 3. are all different 4. The mean VIQ scores for the younger, middle-aged, and older subjects are all different from each other 5. The mean VIQ scores for the younger, middle-aged, and older subjects are not equal to one another 6. The mean VIQ scores for the younger, middle-aged, and older subjects are not the same as each other
A group of boys believe that there is a relationship between the act of sending flowers to a girl and texts received as a result. A study was carried out in which a sample of girls were asked whether they received any flowers and how many texts they sent in response. a)What type of variable is the explanatory variable? Quantitative Categorical b) What type of variable is “number of texts sent in response?” Categorical Quantitative c)What type of visual display should be used to summarize this data? Bar chart Side-by-side boxplots Histogram Dot plot
The Bureau of Labor Statistics reports that the official unemployment rate for Black people was 10.4% and 4.7% for White people in February 2015. Select all correct answers for this question. O The samples of white and black people are independent. The explanatory variable is the unemployment rate. The response variable is the unemployment rate. The response variable is race.
Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season acer
Mike would like to find out if a new intervention would increase the motivation to study chemistry in high school students. He recruits 40 high schoolers and gives the intervention to 20 of the students. He then measures attitudes towards studying chemistry in all the students and compares the results for the students who got the intervention with the students who did not. Mike's study... A. Has a non-directional hypothesis and should be tested with a dependent samples t- test B. Has a non-directional hypothesis and should be tested with an independent samples t-test C. Has a directional hypothesis and should be tested with an independent samples t-test D. Has a directional hypothesis and should be tested with an dependent samples t-test
In 2001, the polls found that 81% of American adults believed that there was a conspiracy in the death of President Kennedy. Assume a recent poll asked 1160 American adults if they believe there was a conspiracy in the assassination and it found that 897 believe there was a conspiracy. Does the data show that the proportion of Americans who believe in this conspiracy is now lower? Test at the 9% level. What is the correct parameter symbol for this problem? What is the wording of the parameter in the context of this problem? Fill in the correct null and alternative hypotheses:

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