STATISTICS 4
Statistics
Statistics
Question1

The dependent variable is the player’s score.

The hypothesis being tested is The score of a golf player is affected by the quality of play of the playing partners

The variable that captures the hypothesis is the Score of the playing partners

The coefficient is 0.035

The meaning of this coefficient is that a player’s score will be affected by a margin of 0.035 of the scores of the playing partner. It shows the extent of change of an individual caused by the score of the playing partners.

It is not at the significant 5% Instead, it is at 0.5%

This means that there is a 0.5% chance of having the wrong value of the coefficient compared to the one given, 0.035.

Would you say that there is good evidence for peer effects? Explain.
Thereis no good evidence for peer effects on the playing partner’s scoreto that of an individual player. This is because the coefficient ofthe equation is low that the change of the score of an individual isinsignificant to the change in the score of the playing partners.

The coefficient on own ability is significant at the 5% level

The type of variable is a constant variable

This estimate means that the score of an individual will be a constant from a person’s ability. The rest of the value for full score will change depending on other factors, such as the
Question2
Tuesday 
Thursday 

Win 
20 
15 
Lose 
8 
13 

If he wrestles better on Tuesday the best statistical test to use is the Null Hypothesis test

The hypothesis to be tested Kobo performs better on Tuesdays than on Thursday

The null hypothesis Kobo does not perform better on Tuesdays than on Thursday

The pvalue, 0.167 obtained from the test shows that Kobo should accept the hypothesis he was testing. It means that he should accept that he performs better on Tuesdays than on Thursdays. This is because the pvalue is higher than the 0.05

What is learned from this test is that the hypothesis is a true hypothesis. The hypothesis of the results provides proves that Kobo is lucky to win more on Tuesdays, just like his name suggests. This is because the pvalue is greater than 0.05, thereby indicating that he should reject the null hypothesis.
Question3
Fromthe bowling exercises of Fred, the following are his dataxxx/xxx/////xxxx////x

The conditional probability of a strike in the frame following a strike is 3/21. In terms of percentage, the probability is 3/21 (100) = 14.29%

The number of runs for Fred are21, with 11 strikes and 10 spares

After the runs test for this data relating to Fred, the Expected Number of Runs: 11.5 with a standard deviation of 2.2279 and a zvalue of 2.0091
Theexpected number of runs shows the total number of outcomes thatexpected results to appear on the same consecutive flips. Thestandard deviation shows the level of deviation from the mean of allthe statistics or outcomes of the bowls. The resulting data does notshow any evidence of the hot hand phenomenon. This is because theprobability of strikes seems to be decreasing as the amount of triesincrease.

The picture of the distribution of runs.