Two surfers and statistics students collected data on the number samples. Test the hypothesis that the mean days surfed for all longboarders is larger than the mean days surfed for all shortboarders (because longboards can go out in many different surfing conditions). Use a level of significance of 0.05. days on which surfers surfed in the last month for 30 longboard (L) users and 30 shortboard (S) users. Treat these data as though they were from two independent random Longboard: 4,10,9,4,9,8,8,6,7,9,11,11,9,15,11,16,13,11,12,18,18,13,12,15,20,22,7,24,22,24 D Shortboard: 6,4,4,6,9,9,6,8,4,8,8,5,9,9,4,16,12,9,13,13,10,13,11,12,14,14,9,21,19,10 Determine the hypotheses for this test. Choose the correct answer below. O A. Ho: HL =Hs Hg: HL # Hs O B. Ho: HL> Hs OC. Ho: PL Ps H: HL =Ps OE. Ho: HL = Hs H: HL> Hs OF. Ho: HL #Hs O D. Ho: PL=Ps H: PL Hs H: PL Ps Find the test statistic for this test. t= (Round to two decimal places as needed.) Find the p-value for this test. p-value = (Round to three decimal places as needed.) %3D What is the conclusion for this test? O A. Do not reject Hn. The mean days surfed for longboarders is not significantly larger than the mean days surfed for all shortboarders O B. Reject Ho- The mean days surfed for longboarders is significantly larger than the mean days surfed for all shortboarders OC. Reject Ho- The mean days surfed for longboarders is not significantly larger than the mean days surfed for all shortboarders O D. Do not reject Ho. The mean days surfed for longboarders is significantly larger than the mean days surfed for all shortboarders
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
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