Recall that for a random variable to be a binomial random variable, you must have an experiment which meets the following three criteria:
1: There are exactly two outcomes for each trial.
2: There are a fixed number (n) of trials.
3: The trials are independent, and there is a fixed probability of success (p) and failure (q) for each trial.

For each of the two situations described below, please indicate if the variable X (as defined in each situation) can be considered a binomial random variable. If you think that X is a binomial variable, please explain how the situation specifically meets each of the three criteria, and identify the values of n and p. If you think X cannot be considered a binomial variable, please indicate which of the three criteria is/are not met (indicate all that apply), and provide a brief explanation for your choice(s). Hint: X can be considered a binomial random variable in only one of the two situations below, but I am not telling you which one, obviously.

Situation 1: A fair coin is tossed over and over again. Let X = the number of tosses until the third TAILS appears.

Situation 2: A box contains 10 marbles: 4 are red, 3 are white, and 3 are blue. A marble is randomly selected, returned to the box, then another marble is randomly selected. Let X = the number of red marbles selected in the two consecutive trials.

A government entity sets a Food Defect Action Level (FDAL) for the various foreign substances that inevitably end up in the foods we eat. The FDAL level for insect filth in peanut butter is 0.70 insect fragment (larvae, eggs, body parts, and so on) per gram. Suppose that a supply of peanut butter contains 0.70 insect fragment per gram. Compute the probability that the number of insect fragments in a 66-gram sample of peanut butter is (a) exactly two. Interpret the results. (b) fewer than two. Interpret the results. (c) at least two. Interpret the results. (d) at least one. Interpret the results. (e) Would it be unusual for a 6-gram sample of this supply of peanut butter to contain four or more insect fragments?

Suppose that the number of gallons of milk sold per day at a local supermarket are normally distributed with mean and standard deviation of 419.9 and 26.93, respectively. What is the probability that on a given day the supermarket will sell between 432 and 438 gallons of milk?

Question 2 options:

During the dry month of August, one U.S. city has measurable rain on average only 3 days per month.

Assume all months have 30 days.

*(Round your answers to 1 decimal place.)
**(Round the intermediate values to 4 decimal places. Round your answer to 4 decimal places.)


(a) If the arrival of rainy days is Poisson distributed in this city during the month of August, what is the average number of days that will pass between measurable rain?
*

(b) What is the standard deviation?
*

(c) What is the probability during this month that there will be a period of less than 3 days between rain?

A) 3

B)1.7

C).6472 IS WHAT I GOT BUT SAYS ITS INCORRECT HELP PLZZZ

A government entity sets a Food Defect Action Level (FDAL) for the various foreign substances that inevitably end up in the foods we eat. The FDAL level for insect filth in peanut butter is 0.8 insect fragment (larvae, eggs, body parts, and so on) per gram. Suppose that a supply of peanut butter contains 0.8 insect fragment per gram. Compute the probability that the number of insect fragments in a 5-gram sample of peanut butter is

(a) exactly two. Interpret the results.

(b) fewer than two. Interpret the results.

(c) at least two. Interpret the results.

(d) at least one. Interpret the results.

(e) Would it be unusual for a 5-gram sample of this supply of peanut butter to contain four or more insect fragments?

A recent study of home internet access reported the following number of hours of internet access per month for a sample of 20 persons [3+4+4+2 points]. 74 81 83 72 76 71 63 66 68 78 76 66 87 54 82 86 90 98 58 92 (a) Use probability plot in MINITAB to check if data are approximately normally distributed. (b) Use MINITAB to construct a 90% confidence interval for the population mean score and interpret your result. (c) Use MINITAB to construct a 95% confidence interval for the population mean scores and interpret your result. (d) Compare part (b) and (c) and explain which confidence interval is narrower and why?

1-Draw the 1s probability densitu function with respect to distance. What happen when two 1S electrons from different atoms interact?

2-Briefly explain how Kronig-Penny Model can be used to explain the existence of band structure

3-Using E-K graph explain what direct and indirect bandgap is

4-Expain how the Fermi-Dirac distribution change from 0K to 100K.

5-Explain why the number of intrinsic hole and electron are similar in the intrinsic semiconductor

6- Explain how PN junction is formed

7- State Poisson equation and explain how the voltage across an PN-junction can be derived

8- Where is the capacitance for a diode coming from?

A government entity sets a Food Defect Action Level​ (FDAL) for the various foreign substances that inevitably end up in the foods we eat. The FDAL level for insect filth in peanut butter is 0.6 insect fragment​ (larvae, eggs, body​ parts, and so​ on) per gram. Suppose that a supply of peanut butter contains 0.6 insect fragment per gram. Compute the probability that the number of insect fragments in a 9-gram sample of peanut butter is

(a) exactly three. Interpret the results.

​(b) fewer than three. Interpret the results.

​(c) at least three.Interpret the results.

​(d) at least one. Interpret the results.

​(e) Would it be unusual for a 9​-gram sample of this supply of peanut butter to contain five or more insect​ fragments?

Complete the statements correctly.

A chance experiment is an experiment where 1) The result is not predetermined 2) The result is predetermine 3) The result is either zero or one,

such as 1) Getting tails when flipping a coin 2) Selecting a card from a deck to see what suit you get 3) Deciding which cereal to buy at the store.

An outcome is 1) The result of one instance of an experiment 2) The probability of one result of an experiment 3) The conclusion drawn about an experiment 4) A type of chance experiment.

The sample space for an experiment is the 1) Population from which the sample is chosen 2) Combination of any number of outcomes 3) Sample of participants used to run the experiment 4) Set of all potential results of the experiment.

In this problem there are two random variables X and Y. The random variable Y counts how many times we roll the die in the following experiment: First, we flip a fair coin. If it comes Heads we set X= 1 and roll a fair die until we get a six. If it comes Tails, we set X= 0 and roll the die until we get an even number (2, 4 or 6).

a). What are the possible values taken by the pair (X,Y)? What is the probability that (X,Y) =(0,k) fork= 1,2,...? What is the join mass distribution function of the pair (X,Y)?

b). What is the mass distribution of the second marginal of (X,Y), that is, the mass distribution of Y?