Q1. If calculated |r| > critical value of r, then there is a linear correlation between the variables. a. True b. False
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.
Q1. If calculated |r| > critical value of r, then there is a
a. True
b. False
Q2. In type I error, the significance level α is the probability of making the mistake of rejecting
the null hypothesis, when it is true
a. True
b. False
Q3. The alternative hypothesis for the following claim: “A car Company claims that its new
SUV car will average at least 50 miles per gallon in the city” is H1: μ > 50.
a. True
b. False
Q4. If a simple random sample of 45 students is selected in a university from a
distributed
a. True
b. False
Q5. With 0.05 significance level, H1: p > 0.5, and the value of test statistic is z = 1.93. Then the
P-value is equal to 0.9732.
a. True
b. False
Q6. If the test statistic for a left-tailed test is z = –1.72, then P-value is 0.9518.
a. True
b. False
Q7. In a
the corresponding observed value of y is 5.
a. True
b. False
STAT101 Assignment 3
Q8. Assume that the data has a normal distribution and the number of observations is greater
than fifty. With a confidence level α = 0.05 for a right-tailed test, the critical � value used to test
a null hypothesis is 1.645.
a. True
b. False
Q9. A null hypothesis is that the
hypothesis is that men have more mean weight than women. The correct way to state the null
hypothesis is H0: �̅1 – �̅2 = 0
a. True
b. False
Q10. For a hypothesis test about a population mean, if the level of significance is 0.05 and the P-
value is 0.50, then we fail to reject the null hypothesis.
a. True
b. False
Q11. If � = 0.8, then r2
= 0.64, which means that 64% of the total variation in y is explained by
regression line.
a. True
b. False
Q12. If 150 households were surveyed out of which 120 households have internet fiber cable,
then sample proportion of households without fiber cable is 0.2.
a. True
b. False
Q13. The null Hypothesis is rejected, if the P-value is larger than significance level.
a. True
b. False
Q14. If a fitted linear regression equation between the variables x and y is ŷ = 8 – x, then the
predicted value of y at x = –2 is equal to 6.
a. True
b. False
Q15. If the original claim says that the mean working hours in a day are same for men and
women in a company. Then symbolically it is represented as μ1 ≠ μ2.
a. True
b. False
Q16. If a regression equation is ŷ = 2x, then slope of this line is equal to 2.
a. True
b. False
Q17. If a regression equation is ŷ = 2x, then y-intercept is equal to 2.
a-true
b-false
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