The building of a hacker rank is one that cost a lot of money and as such the minimum cost is 4.
What is the minimum cost?
The minimum cost is the lowest cost that is needed to complete a building. It depends on:
- The cost of each type of house to be built (e.g. cost of a wood house, cost of a brick house, etc.)
- The number of the type of house to be built e.g. 2 03 3 or even more.
When one is given input such as : [[1,2,3],[1,2,3],[3,3,1]] (the values in column stands for the cost of materials)
The output : 4
So you have to:
Select material-1 of cost 1 in first house(row)
Select material-2 of cost 2 in second house(row)
Select material-3 of cost 1 in third house (row)
total = 1+2+1 -> 4
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Answer:
The easiest way to test if water is acidic is to use litmus paper. Litmus paper is a paper that contains special dyes that will change color when exposed to acids or bases. In your case, if you dip blue litmus paper into water samples and it turns pink or red, then the water is acidic.
Answer:
- No, the points are evenly distributed about the x-axis.
Explanation:
<u>1. Write the table with the data:</u>
x given predicted residual
1 - 3.5 - 1.1
2 - 2.9 2
3 - 1.1 5.1
4 2.2 8.2
5 3.4 1.3
<u>2. Complete the column of residuals</u>
The residual is the observed (given) value - the predicted value.
- residual = given - predicted.
Thus, the complete table, with the residual values are:
x given predicted residual
1 - 3.5 - 1.1 - 2.4
2 - 2.9 2 - 4.9
3 - 1.1 5.1 - 6.2
4 2.2 8.2 - 6.0
5 3.4 1.3 2.1
<u>3. Residual plot</u>
You must plot the last column:
x residual
1 - 2.4
2 - 4.9
3 - 6.2
4 - 6.0
5 2.1
See the plot attached.
<em>Does the residual plot show that the line of best fit is appropriate for the data?</em>
Ideally, a residual plot for a line of best fit that is appropiate for the data must not show any pattern; the points should be randomly distributed about the x-axis.
But the points of the plot are not randomly distributed about the x-axis: there are 4 points below the x-axis and 1 point over the x-axis: there are more negative residuals than positive residuals. This is a pattern. Also, you could say that they show a curve pattern, which drives to the same conclusion: the residual plot shows that the line of best fit is not appropiate for the data.
Thus, the conclusion should be: No, the points have a pattern.
- 1. "<em>Yes, the points have no pattern</em>": false, because as shown, the points do have a pattern, which makes the residual plots does not show that the line of best fit is appropiate for the data.
- 2. "<em>No, the points are evenly distributed about the x-axis</em>": true. As already said the points have a pattern. It is a curved pattern, and this <em>shows the line of best fit is not appropiate for the data.</em>
- 3. "<em>No, the points are in a linear pattern</em>": false. The points are not in a linear pattern.
- 4. "<em>Yes, the points are in a curved pattern</em>": false. Because the points are in a curved pattern, the residual plot shows that the line of best fit is not appropiate for the data.
Answer:
C- 15 square units
Explanation:
3/2=1.5
10 x 1.5 =15 square units
Answer:
Internal citations provide the author and page number of the source, while the Works Cited provides all publication information.
Explanation:
hope this helps you