Suppose one gallon of gasoline produces 1.24×108 J of energy, and this energy is sufficient to operate a car for 20.8 miles. An aspirin tablet has a mass of 339 mg. If the aspirin could be converted completely into thermal energy, how many miles could the car go on a single tablet?

1. Choose the scenario under which each of the following Doppler shift effects will be seen:

choices are:

The source and observer are approaching one another

The source and observer are moving away from one another

The source and observer are stationary relative to one another

1.1 Light is shifted towards the blue end of the spectrum (blue-shifted).

1.2 The apparent pitch of the source is lower than the actual pitch of the source.

1.3 There is no apparent change in the pitch or color.

1.4 Light is shifted towards the red end of the spectrum (red-shifted).

1.5The apparent pitch of the source is higher than the actual pitch of the source.

2.Sounds coming from moving objects, such as the siren of an emergency vehicle, appear to change pitch as the object moves toward or away from you. Compare the frequency of a siren based on its motion toward or away from you.

rate from  highest to lowest

away from you 31 miles per hour

toward you at 34 miles per hour

away from you at 34 miles per hour

toward you at 55 miles per hour

neither toward nor away from you

toward you at 3 miles per hour

The Indiana State Police union is interested in whether the number of miles driven by each trooper is the same or different for the three different 8-hour shifts. Twenty Indiana state troopers were selected randomly selected on each of the three shifts and the number of miles that they traveled was recorded.

a) Is this an observational or an experimental study? Please explain your answer.

b) What is the population in this study?
20 Indiana troopers in each shift.
All police officers
The recorded number of miles
The times of the shift.
The Indiana State Police union
All Indiana State Troopers

c) What is the factor or treatment in this study?
All police officers
20 Indiana troopers in each shift.
All Indiana State Troopers
The times of the shift.
The Indiana State Police union
The recorded number of miles

d) What is the outcome variable of this study?
The Indiana State Police union
All Indiana State Troopers
The recorded number of miles
20 Indiana troopers in each shift.
The times of the shift.
All police officers

e) State a possible source of bias in this study. Feel free to speculate beyond the explicit statement of the question. However, nothing that is assumed can be contradicted by what is stated. Please include any assumptions that you are making.

A tire manufacturer warranties its tires to last at least 20 comma 000 miles or​ "you get a new set of​ tires." In its​ experience, a set of these tires last on average 28 comma 000 miles with SD 5 comma 000 miles. Assume that the wear is normally distributed. The manufacturer profits ​$200 on each set​ sold, and replacing a set costs the manufacturer ​$400. Complete parts a through c.

​(a) What is the probability that a set of tires wears out before 20 comma 000 ​miles? The probability is nothing that a set of tires wears out before 20 comma 000 miles. ​(Round to four decimal places as​ needed.)

​(b) What is the probability that the manufacturer turns a profit on selling a set to one​ customer? The probability is nothing that the manufacturer turns a profit on selling a set to one customer. ​(Round to four decimal places as​ needed.)

​(c) If the manufacturer sells 500 sets of​ tires, what is the probability that it earns a profit after paying for any​ replacements? Assume that the purchases are made around the country and that the drivers experience independent amounts of wear. The probability is nothing that the manufacturer earns a profit after paying for any replacements on 500 sets of tires. ​(Round to four decimal places as​ needed.)

I am having a trouble with a python program. I am to create a program that calculates the estimated hours and mintutes. Here is my code.

#!/usr/bin/env python3
#Arrival Date/Time Estimator
#
#

from datetime import datetime
import locale

mph = 0
miles = 0
def get_departure_time():
    while True:
        date_str = input("Estimated time of departure (HH:MM AM/PM): ")
        try:
            depart_time = datetime.strptime(date_str, "%H:%M %p")
        except ValueError:
            print("Invalid date format. Try again.")
            continue
        return depart_time

def get_departure_date():
    while True:
        date_str = input("Estimated date of departure (YYYY-MM-DD): ")
        try:
            depart_date = datetime.strptime(date_str, "%Y-%m-%d")
        except ValueError:
            print("Invalid date format. Try again. ")
            continue
        return depart_date
  
def travel_calculations():

      Estimated_travel_time = (miles / mph)
      a=timedelta(hours=Estimated_travel_time)
      a=str(a)
      a=a.split(':')
      print (" The estimated travel time: ",a[0],'hours and ', a[1],'minutes')

def main():
    print("Arrival Time Estimator\n")
    depart_time = get_departure_time()
    depart_date = get_departure_date()
    travel_calculations()
    miles = input("Enter miles: ")
    mph = input("Enter miles per hour : ")
    return

if __name__ == "__main__":
    main()

Suppose you have ridden a bicycle from New York City to Key West, Florida. Your bicycle odometer shows the total miles you have travelled thus far, which you make a note of each day with paper and pencil. Your first two entries might be ‘55’ and ‘120’, indicating that you rode your bike 55 miles on day 1 and 65 miles on day 2. Your task is to create a NumPy array wherein you can record the cumulative miles you recorded each day during your trip “by hand”. Then use your Python skills to show the total miles that you rode each day. Assume the trip took a total of 35 days and included at least 4 non-consecutive days where no cycling was possible due to either weather conditions or personal fatigue/soreness. For the remaining 31 days, you would have covered the entire distance between NYC and Key West. Complete your work within your Jupyter Notebook for this assignment and be sure to include a writeup explaining your approach to this problem, including the ways in which you decided to make use of NumPy.

The developer of a new filter for filter-tipped cigarettes claims that it leaves less nicotine in the smoke than does the current filter. Because cigarette brands differ in a number of ways, he tests each filter on one cigarette of each of nine randomly selected brands and records the difference in nicotine content. His results are given in the table below.

Does the data give convincing evidence that the filter tips leave less nicotine in the smoke? Follow the 4-step process.

old=c(.7, .8, .8, .9, .9, 1, 1.2, 1.2, 1.8)

new=c(.6, .6, .7, .8, .7, 1, .8, .9, 1.5)

YOU MUST FOLLOW THE 4-STEP PROCESS

STATE:

PLAN:

DO:

CONCLUSION:

Thank you!

2. A. Find the five-number summary for the Tar content of the sample of cigarettes. List the values. Draw a boxplot to illustrate this. Be sure to show an evenly marked scale below it. Use a ruler to draw the figure. Comment on its shape, i.e. does it appear to be skewed left, skewed right, or symmetrical? B. Compute the IQR, UF, and LF for the Tar content of the sample of cigarettes. Does the data have any outliers? If so, list them. C. State the mode(s) of the tar content. D. Compute the range of the tar content.

Cigarette Data (all quantities are in mg per cigarette)