Answer:
A.Big,Rectangular
Explanation:
mile markers are sign on high ways they are green signs they are big and rectangular shape
Answer:
Following are the correct python code to this question:
n1 = float(input('Input first number: '))#input first number
n2 = float(input('Input second number: '))#input second number
n3 = float(input('Input third number: '))#input third number
n4 = float(input('Input fourth number: '))#input fourth number
average = (n1+n2+n3+n4)/4 #calculate input number average
product = n1*n2*n3*n4 # calculate input number product
print('product: {:.0f} average: {:.0f}'.format(round(product),round(average))) #print product and average using round function
print('product: {:.3f} average: {:.3f}'.format(product,average)) #print product and average value
Output:
Please find the attachment.
Explanation:
The description of the above python code can be defined as follows:
- In the above python program four variable "n1, n2, n3, and n4" is defined, in which we take input from the user end, and in these user inputs we use the float method, that converts all the input value in to float value.
- In the next step, two variable average and product are defined, that calculate all input numbers product, average, and hold value in its variable.
- In the last line, the print method is used, which prints its variable value by using a round and format method.
Answer:
Step 1 : Create an Indicator Variable for metro cities using formula mentioned in formula bar.
Step 2: Filter the Data on Metro cities i.e. select only those cities with Metro Indicator 1.
Step 3: Paste this filtered data to a new sheet.
Step 4: Go to Data - Data Analysis - Regression
Step 5: Enter the range of Y-variable and X-variable as shown. Select Output range and click on residuals. It will give you Output Summary and the Predicted Values along with Residuals
Please see attachment
Answer:
knowledge acquisition facility
Explanation:
In the context of the components of a typical expert system, Knowledge acquisition facility is defined as that component of an expert system that is responsible for providing an effective and efficient medium for collecting and incorporating relevant information such as data, new rules, relationships and facts used by the expert system.