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algol [13]
4 years ago
5

What happens to the median, mode, and standard deviation when 3 is added to every value in a data set?

Mathematics
1 answer:
GrogVix [38]4 years ago
6 0
Adding a constant to each value in a data set does not change the distance between values so the standard deviation remains the same.
For example, consider the following numbers
2
,
3
,
4
,
4
,
5
,
6
,
8
,
10
for this set of data the standard deviation would be
s
=
√
∑
n
i=1
(
x
i
−
¯
x
)
2
n
−
1
s
=
√
(
2
−
5.25
)
2
+
(
3
−
5.25
)
2
+
...
+
(
10
−
5.25
)
2
8
−
1
s
=
2.65922
If we were to add 5 to each value in this data set, the new set of values would be:
7
,
8
,
9
,
9
,
10
,
11
,
13
,
15
s
=
√
(
7
−
10.25
)
2
+
(
8
−
10.25
)
2
+
...
+
(
15
−
10.25
)
2
8
−
1
s
=
2.65922
As you can see the s.d. remains the same unless you multiply every value by a constant.
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A school authority claims that the average height of students is 178 cm. A researcher has taken a well-designed survey and his s
Hunter-Best [27]

Answer:

d) The difference exists due to chance since the test statistic is small

Step-by-step explanation:

From the given information:

Population mean = 178 cm

the sample mean = 177.5 cm

the standard deviation = 2

the sample size = 25

The null hypothesis and the alternative hypothesis can be computed as:

Null hypothesis:

H_o: \mu = 178

Alternative hypothesis:

H_1: \mu \neq 178

The t-test statistics is determined by using the formula:

t = \dfrac{X - \mu}{\dfrac{\sigma}{\sqrt{n}}}

t = \dfrac{177.5 - 178}{\dfrac{2}{\sqrt{25}}}

t = \dfrac{-0.5}{\dfrac{2}{5}}}

\mathbf{t= -1.25}

Degree of freedom df = n- 1

Degree of freedom df = 25 - 1

Degree of freedom df = 24

At the level of significance ∝ = 0.05, the critical value  = 2.064

Decision rule: To reject the null hypothesis if the test statistics  is greater than the critical value at 0.05 level of significance

Conclusion: We fail to reject the null hypothesis since the test statistics is lesser than the critical value and we conclude that  the difference exists due to chance since the test statistic is small

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