1. Many of the continuous random variables that occur in real life are approximately normally distributed. How do you think this helps in studying real life variables? 2. Do you realize and understand the advantage of being able to convert values of an arbitrary normally distributed random variable to the corresponding values of the standard normal variable? If yes, list all the possible advantages of being able to do this. If not what do you plan to do to understand why the standard normal random variable is widely used for computations involving normal distributions?

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Step-by-step explanation:

3.4 pizzas

step-by-step explanation:

given is a scatter plot showing number of pizzas sold during weeks for different issues of coupon

y represents number of pizzas sold and x number of coupons issued

y is marked verticaly and x horizontally

the trend line is given as

y =3.4x+43

this says that even when no coupon is issued pizzas sold will be 43

and rate of change of pizza sold for 1 unit of coupon = slope = 3.4

i.e. when x increases by 1 unit y increases by 3.4 units

hence for each additional coupon issued 3.4 pizzas more will be sold

  q

step-by-step explanation:

each line from a vertex to the midpoint of the opposite side is called a median. the point where the medians intersect, point q, is the centroid.

the centroid of δabc is point q.