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3 years ago

What is are the disadvantages of being so friendly with people

SAT

2 answers:

riadik2000 [5.3K]3 years ago

6 0

Answer:

People often take advantage of you
People often pressure you to do things you don't want to
Some friends aren't really your friends
People bribe you very often

nasty-shy [4]3 years ago

5 0

Answer:

You attract the wrong kind of people

You attract the wrong kind of peopleBe excessively nice and "you will start to attract needy, whiny, overly emotional, demanding/controlling, 'guilt tripping you if you don't do something for them' types of people," she writes.

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The two structures that limit transpiration are known as

Lady_Fox [76]

Leaf stomates are the primary sites of transpiration and consist of two guard cells that form a small pore on the surfaces of leaves. The guard cells control the opening and closing of the stomates in response to various environmental stimuli and can regulate the rate of transpiration to reduce water loss.

8 0

2 years ago

Synonym for inculcated

astraxan [27]

Answer:

instill, implant, ingrain, imprint, impress

7 0

3 years ago

Find the residual values, and use the graphing calculator tool to make a residual plot.

finlep [7]

Answer:

No, the points are evenly distributed about the x-axis.

Explanation:

1. Write the table with the data:

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

2. Complete the column of residuals

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

3. Residual plot

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.

Does the residual plot show that the line of best fit is appropriate for the data?

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. "Yes, the points have no pattern": 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. "No, the points are evenly distributed about the x-axis": true. As already said the points have a pattern. It is a curved pattern, and this shows the line of best fit is not appropiate for the data.

3. "No, the points are in a linear pattern": false. The points are not in a linear pattern.

4. "Yes, the points are in a curved pattern": 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.