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Vilka [71]
3 years ago
14

* ae. This number in unit form is all mixed up! Convert it to standard form. 4 hundred thousands 16 thousands 4 hundreds 21 tens

12 ones​
Mathematics
1 answer:
DiKsa [7]3 years ago
7 0

Answer: 416, 622

Step-by-step explanation:

First, let's look at the hundred thousands place.

We have 4 hundred thousand, which can be rewritten as 400,000.

Then, we have our ten thousand place in which we have sixteen thousand, which can be rewritten as 16,000.

Next, we have our hundreds place. Here, we have four-hundred, or 400.

After that, we have 21 tens, which can be rewritten as 210.

Lastly, we have 12 ones.

Now, if we add all of these together, we get:

400,000 + 16,000 + 400 + 210 + 12 = <em>416,622</em>

(Hope this helps!)

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Answer:

2/1

Step-by-step explanation:

8/4 which is also 2/1

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3 years ago
The table shows the number of medical clinics and the number of bowling alleys in several cities.
DedPeter [7]

Answer:

Step-by-step explanation:

a) to create a scatter plot for the data, let data for clinics be x and that one for Bowling alleys be y then plot x values with corresponding y values on a graph tool.

<u>x                     y</u>

14                   12

1                      3

6                     6

5                     7

10                    7

6                      8

11                      9

8                      15

6                       7

16                     12

The scatter plot is attached below

b) a cluster is a group of data that is close together. From the plot, the ordered pairs forming a cluster are;

(6,6), (6,7), (5,7), and (6,8)

c) An outlier is a point in a plot which lies very far from the other values. In this case, point its  point (8,15)

d)The linear regression equation is one written in the form of

Y=a+bX where ;

Y=the dependent variable

X=the explanatory variable

a=the intercept, which is the value of y when x=o

b=slope of the line

The formula to apply here is ;

a=(∑y)(∑x²)-(∑x)(∑xy) / n(∑x²)-(∑x)² where n is number of samples

b= n(∑xy)-(∑x)(∑y) / n(∑x²)-(∑x)²

Form a table like below

<u>x                     y               xy               x²                 y²</u>

14                   12              168            196              144

1                      3                 3               1                   9

6                     6                 36            36                 36

5                     7                 35             25                49

10                    7                 70             100              49

6                      8                 48             36              64

11                      9                99             121               81

8                      15               120             64            225

6                       7                42               36              49

16                     12                192            256            144

83                     86              813           871               850------------sum

∑x=83   ∑y=86  ∑xy=813  ∑x²=871  ∑y²=850 and n=10

Applying the formula

a=(∑y)(∑x²)-(∑x)(∑xy) / n(∑x²)-(∑x)²

a=[(86 * 871) - (83*813) ]/ 10 (871-83²)

a=[74906 - 67479] / 10(-6018)

a=[7427] / -60180

a= - 0.1234

b= n(∑xy)-(∑x)(∑y) / n(∑x²)-(∑x)²

b=10(813)-(83*86) / 10 (871)-(83²)

b=[8130-7138] / 8710 -6889

b= 992/1821

b=0.5448

The liner regression equation will be;

Y=a+bX

Y= -0.1234 + 0.5448 X

e) correlation coefficient r is given by;

r= n∑xy - (∑x)(∑y) / √n(∑x²)-(∑x)² × √n(∑y²)-(∑y)²

r=10*813 - (83*86) / √10 *871 -83² ×√10*850 - 86²

r=8130-7138 / √8710-6889 × √8500-7396

r= 992 / (√1821 × √1104)

r=992/ 42.67×33.23

r=992/1417.9

r=0.6996

f) r² is important because it shows you the proportion of the variance of one variable that is predictable from the other variable.

r=0.6996

r²=0.6996² =0.4894

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