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Keith_Richards [23]
2 years ago
15

In a set of 10 observations the mean is 20 and the median is 15. There are 2 values that are 6, and all other values are differe

nt. What is the mode?
Mathematics
1 answer:
Kitty [74]2 years ago
7 0

The mode of the set of 10 observations is 2.

What is the mode?

Mode refers to a value that appears most frequently in a data set. Mode is a measure of central tendency of a data set. Other measures of central tendency are mean and median.

According to the information in the question, 6 appears twice in the data set and all other values are different. Thus, 6 has the frequency of 2 which is the highest. 6 is the mode.

To learn more about mode, please check: brainly.com/question/16505756

#SPJ1

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Answer:

10/8 or 1 and 2/8

Step-by-step explanation:

You can convert 2/4 into 4/8 then all you have to do from there is just add to get 10/8.

Hope I could help! :)

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The y-intercept in the linear equation y=−110x−2 is _[blank]_.
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-2

Step-by-step explanation:

This linear equation is in slope-intercept format, aka y=mx+b. This is where m=slope and b=y-intercept. In the following equation, -110 is the slope and -2 replaces b, meaning it is the y-intercept

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A study of the relationship between age and various visual functions (such as acuity and depth perception) reported the followin
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Answer:

(a) \sum x_i=56.68 and \sum x_i^2=197.46

(b) The sample variance is s^2=0.530 and the sample standard deviation is s=0.728

Step-by-step explanation:

(a)

The sum of these 17 sample observations is

\sum x_i=2.79\:+2.57+\:2.73\:+3.75\:+2.27+\:2.75+\:4.00+\:4.22+\:3.88+\:4.35+\:3.41+\:4.57+\:2.38+\:3.73\:+2.75+\:3.47+\:3.06\\\\\sum x_i=56.68

and the sum of their squares is

\sum x_i^2=2.79^2\:+2.57^2+\:2.73^2\:+3.75^2\:+2.27^2+\:2.75^2+\:4.00^2+\:4.22^2+\:3.88^2+\:4.35^2+\:3.41^2+\:4.57^2+\:2.38^2+\:3.73^2\:+2.75^2+\:3.47^2+\:3.06^2\\\\\sum x_i^2=197.46

(b)

The sample variance, denoted by s^2, is given by

s^2=\frac{S_{xx}}{n-1}

where S_{xx} =\sum x_i^2-\frac{(\sum x_i)^2}{n}

Applying the above formula we get that

S_{xx}=197.46-\frac{(56.68)^2}{17}\\\\S_{xx} =8.482

s^2=\frac{8.482}{17-1}=0.530

The sample standard deviation, denoted by <em>s</em>, is the (positive) square root of the variance:

s=\sqrt{s^2}

Applying the above formula we get that

s=\sqrt{0.530}=0.728

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