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babunello [35]
3 years ago
10

Pls help I dont under stand this at all

Mathematics
1 answer:
lisabon 2012 [21]3 years ago
7 0

Answer:

0.5 = 0.25

1=2

2=4

2.5=5

3=6

Step-by-step explanation:

distance divided by 2 equals the time

i hope this helps!

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Ellen saved $2000 and she spent 10% of it to buy a bike. Kim saved 8% more than that of Ellen's left savings. If Lisa saved 60%
enyata [817]

Answer: Lis saved $1166.4 .

Step-by-step explanation:

Given , Ellen saved $2000 and she spent 10% of it to buy a bike.

Then, Ellen's left saving = saved amount - 10% of  (saved amount)

= $2000 - 0.10 x $2000 <em>[We convert perecntage to decimal by diving it by 100]</em>

= $2000 - $200

= $1800

So, Ellen's left saving= $1800

Also, Kim saved 8% more than that of Ellen's left savings.

Kim's Saving = Ellen's left saving + 8% of (Ellen's left saving)

= $1800  + (0.08) x ($1800) <em>[We convert perecntage to decimal by diving it by 100]</em>

= $1800 +  $144

i.e. Kim's Saving= $1944

If Lisa saved 60% as much as Kim, then Lisa's saving  = 60% of (Kim's Saving)

= (0.60) x ($1944) <em>[We convert perecntage to decimal by diving it by 100]</em>

i.e. Lisa's saving = $1166.4

4 0
3 years ago
What is the ansser <br><br><br> plase help
aniked [119]

Answer:

sir this isnt math

Step-by-step explanation:

put it in spanish next time

5 0
3 years ago
Read 2 more answers
Please Help! <br> Factor the expression:<br> x2 − 28x + 52
Drupady [299]

Answer:

(x-2)(x-26)

Step-by-step explanation:

x^2-2x-26x+52

x(x-2)-26(x-2)

(x-2)(x-26)

8 0
4 years ago
Read 2 more answers
POSSIBLE PC
bixtya [17]
I think it will be The seconds one so B
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3 years ago
a farmer wishes to test the effects of a new fertilizer on her wheat yield. she has four equal-sized plots of land-- one with sa
Fofino [41]

Using the concept of Randomized Design ,we got 4 levels of treatment heave been done by farmer in this experiment.

1.Completely Randomized Design :-

A completely randomized design is basically the simplest experimental design, in terms of data analysis and convenience. With this design, subjects are randomly assigned to treatments.

This completely randomized design actually relies on randomization to control for the effects of extraneous variables. The experimenter actually assumes that, on average, extraneous factors will affect treatment conditions equally; so any relevant differences between conditions can fairly be attributed to the independent variable.

2.Double Blind Design :-

In an experiment, if subjects in the control group knows that they are receiving a placebo, the placebo effect will be reduced or will be eliminated; and the placebo will not serve its intended control purpose.

Blinding is basically the practice of not telling subjects whether they are receiving a placebo. In this way, subjects which are in the control and treatment groups experience the placebo effect equally. Often, knowledge of which groups receive placebos is also keep from analysts who evaluate the experiment. This practice is called double blinding. It prevents the analysts from "spilling the beans" to the subjects through subtle cues; and it assures that their evaluation is not tainted by the awareness of actual treatment conditions.

3.Matched Pairs Design :-

A matched pairs design is actually a special case of a randomized block design. It can be used when the experiment has basically only  two treatment conditions; and subjects can be grouped into pairs, on the basis of some blocking variable. Then, within each pair, subjects are randomly assigned to different treatments.

4.Randomized Block Design :-

With a randomized block design, the experimenter actually divides subjects into subgroups called blocks, such that the variability within blocks will become  less than the variability between blocks. Then, subjects within each block are randomly assigned to treatment conditions.

Hence, we got 4 levels of treatment have been done by farmer in this experiment.

To know more about Randomized Design ,visit here:

brainly.com/question/17128981

#SPJ4

5 0
1 year ago
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