Question 2 The probability of getting a multiple choice question wrong is 0.8. A weekly quiz has 10 multiple choice questions. Assume independence between the questions a) What is the probability of getting 5 questions correct? b) What is the probability of getting 5 questions wrong? c) What is the probability of getting at least 8 questions correct? d) What is the probability of getting more than 8 questions correct? e) What is the probability that you will get a zero in the quiz?

Q: Thank you for your help. I got the same answer for (b) and (c), but both were found to be wrong,…

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A: Given that Lourdes get 80% in her test. Total number of questions = 50 Number of questions she did…

Q: I need help solving for parts a-c

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Q: please provide solutions for part d and e of the question

A: It is given that  Total = 75 Number of matches with good weather = 33 Number of matches win = 26…

Q: Thanks for the help! I was also wondering how I would know that the answer would be meaningful?

A: Firstly understand,  Y-intercept :  it is mean value of y when all predictors (x) equals to 0. X=…

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Q: The rest of the questions here please, thank you!

A: As per Bartleby guidelines we only give first three questions answers. Please repost for other…

Q: 3 6. Find x. 4

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Q: The answer

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Q: Hw.

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Q: 3. The data in Table 7–7 were collected in an experiment designed to investigate the impact of…

A: Since you have asked multiple questions, we will solve the first question for you. If you want any…

Q: Does the solution it address the three additional people drawing?

A: It is related to binomial probability : P(X=x) = nCx*px*qx    p= 12/52 = 0.23 q= 1-(12/52) = 0.77

Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.