Match the scenario to the related government program.

How does warming up the tires on a car increase grip with the pavement?

ICE Princess25 [194]

Answer:

because burning rubber increases the grip power

8 0

2 years ago

Suggest appropriate materials for a cylinder head and give four reason for your choice

ycow [4]

Answer:

head and give four reason for your choice

7 0

3 years ago

Which examples demonstrate tasks commonly performed in Maintenance/Operations jobs? Check all that apply.

Verdich [7]

1.Ross fixes a dishwasher for a homeowner.

3.Cassandra fixes holes in an old road.

4 0

3 years ago

Read 2 more answers

At 45° latitude, the gravitational acceleration as a function of elevation z above sea level is given by g = a − bz , where a =

Ahat [919]

Answer:

8861.75 m approximately 8862 m

Explanation:

We need to remember Newton's 2nd Law which says that the force experienced by an object is proportional to his acceleration and that the constant of proportionality between those two vectors correspond to the mass of the object.

$F=ma$ for the weight of an object (which is a force) we have that the acceleration experienced by that object is equal to the gravitational acceleration, obtaining that $W = mg$

For simplicity we work with $g =9.807$ $\frac{m}{s^{2}}$ despiting the effect of the height above sea level. In this problem, we've been asked by the height above sea level that makes the weight of an object 0.30% more lighter.

In accord with the formula $g = a-bz$ the "normal" or "standard" weight of an object is given by $W = mg = ma$ when $z = 0$ , so we need to find the value of $z$ that makes $W = m(a-bz) = 0.997ma$ meaning that the original weight decrease by a 0.30%, so now we operate...

$m(a-bz) = 0.997ma$ now we group like terms on the same sides $ma(1-0.997) = mbz$ we cancel equal tems on both sides and obtain that $z = \frac{a}{b} (0.003) = \frac{9.807 \frac{m}{s^{2} } }{3.32*10^{-6} s^{-2} } (0.003) = 8861.75 m$

7 0

3 years ago

Let's model this housing price data! Before we can do this, however, we need to split the data into training and test sets. Reme

Lilit [14]

The program reads in a dataset into a pandas dataframe, and uses the train_test_split function in the sklearn library to split the data into training and test sets. The code goes thus :

import pandas as pd

#import the pandas dataframe and alias it as pd

from sklearn.model_selection import train_test_split

#import the train_test_split function

housing_df = pd.read_csv('housing price.csv')

#read in the housing data

features_df = df.iloc[:,1:]

#seperate the features from the label ;

target_df = df.iloc[:,0]

#put the label into a seperate dataframe as well.

X_train, X_test, Y_train, Y_test = train_test_split(features_df, target_df, test_size = 0.1, random_state = 1)

#uses tuple unpacking to randomly assign the data each of the 4 variables.

#Test size is test percent of the entire dataset

Learn more :brainly.com/question/4257657?referrer=searchResults

3 0

2 years ago