22 = 26 – 4. pg. 109. Correct answer is E.

Ordinal scales of measurement have the property of both classifying and magnitude. Subjects are categorized into different rank ordered groups. Each value on the ordinal scale has a unique meaning, and it has an ordered relationship to every other value on the scale. From the table,  we can conclude that the customer prefers historical fiction to science fiction, science fiction to detective fiction, detective fiction to romance. However, even though the differences in the consecutive numbers of the ranks are equal, we cannot say that how much the customer prefers one type of book over another type. That is, consecutive categories do not represent equal differences of the measured attribute.

All the six letters i­n the gi­ven word were d­ifferent, the total number of arrangements would be 6!.

6!=720

We have to first compute the mean of the distribution in order to calculate the variance.

Mean=Sum(X.P(X=x))=(1*0.1)+(2*0.2)+(3*0.1)+(4*0.3)+(5*0.2)+(6*0.1)

=0.1+0.4+0.3+1.2+1+0.6=3.6

Variance=Sum(P(X)*(X-Mean)²)=0.1*(1-3.6)²+0.2*(2-3.6)²+0.1*(3-3.6)²+0.3*(4-3.6)²+0.2*(5-3.6)²+0.1*(6-3.6)²=2.24

f (x) = ? e^–?x = a e^–ax , x ? 0 ; P( X >= x) = Int(b, sonsuz)(a * e^-at dt) = girdi(b, sonsuz)(-e^-ax) = 0 - (-e^-ab) = e^-ab . pg. 213. Correct answer is D.

The answer is C

The empirical probability uses the relative frequencies to assign the probabilities to the events. The empirical probability is based on experiments. In order to find the probability of a specific event, the experiments are repeated many times and the observed outcomes of the event we are interested in is counted. The correct answer is E.

In order to prove whether tea has an effect on heart diseases, an experiment needs to be conducted where conditions are controlled.

We know that event B has occurred and we are interested in finding the probability of event A. That is, we are interested in finding the probability of A knowing that event B has occurred.The formula for this is as follows: P(A∩B) = P(A⏐B)P(B)

Discrete random variables have only a countable number of separate values such as 0, 1, 2 , 3... etc. For example, the number of students in a class for certain day or the number of customers in a supermarket after 5:00 PM are cases for discrete random variables since these variables are finite and countable. Conversely, continuous random variable can take entire infinite values in a given interval. Because of this reason, continuous random variables are commonly measured instead of counted. For instance, waiting time for customers in a supermarket cashier line and travel time of a bus between two points are examples for continuous random variables. The correct answer is E.

Discrete random variables have only a countable number of separate values such as 0, 1, 2 , 3... etc. For example, the number of students in a class for certain day or the number of customers in a supermarket after 5:00 PM are cases for discrete random variables since these variables are finite and countable. Conversely, continuous random variable can take entire infinite values in a given interval. Because of this reason, continuous random variables are commonly measured instead of counted. For instance, waiting time for customers in a supermarket cashier line and travel time of a bus between two points are examples for continuous random variables. The correct answer is E.

When two coins are tossed at once, some of the possibilities of head or tail can be listed as below:

H(Head) T(Tail)

HHH

TTT

HHT

HTT

When these possibilities are taken into consideration either two or three coins may have the same match. So {2,3}

is the correct answer. 

The measures of skewness are another kind of descriptive statistics and give information about the shape of distribution of the observations. A data set which is not symmetrically distributed is called skewed. The correct answer is A.

Empirical Probability of an Event = The number of times the event happens/Total number of observations

P (Number 4)= 450 / 3000 =0,15

For the calculation of the mean and the variance for the continuous random variables,only difference is integration substitute’s summation. The mean of the continuous random variable is denoted by µ, the mean is also called as expected value and denoted by E (x). The variance is denoted by V (x) or ?2 and it’s a measure of the scatter or variability for data set.  the mean of a continuous random variable X is a weighted average through the possible values of the random variable and associated probabilities. Also, the variance of a continuous random variable X is all squared deviations are weighted with associated probability.