Help :::))) ;) asapppppp :)
1 answer:
You might be interested in
Answer:
a) <em>"K" is proportional Constant K= 0.0833</em>
<em>b) The value of b = 99.639</em>
Step-by-step explanation:
<u><em>Explanation</em></u> :-
Given 'a' is directly proportional to 'b'
a ∝ b
<em> a = k b ....(i)</em>
<em>where "K" is proportional Constant</em>
<u><em>Case(i)</em></u><em>:-</em>
<em>when a =6 and b=72</em>
<em> a = k b </em>
<em> ⇒ 6 = k (72)</em>
<em> ⇒ </em><em> </em>
<u><em>Case(ii)</em></u><em>:- </em>
<em> Given a = 8.3 </em>
<em> a = k b </em>
<em>⇒ 8.3 = 0.0833 ×b</em>
<em>⇒ </em><em></em>
<u><em>Final answer</em></u><em>:-</em>
a)<em>"K" is proportional Constant K= 0.0833</em>
<em>b) The value of b = 99.639</em>
<em></em>
<em></em>
<em></em>
<em></em>
There appears to be a positive correlation between the number of hour spent studydng and the score on the test.
When identifying the independent and dependent quantities, we think about what would cause the other to change. The score on the test would not cause the number of hours spent studying to change; rather, the number of hours spent studying would cause the score to change. This means that the number of hours studying would be the independent quantity and the score would be the dependent quantity.
Plotting the graph with the time studying on the x-axis (independent) and the score on the y-axis (dependent) gives you the graph shown. You can see in the image that there seems to be a positive correlation; the data seem to generally be heading upward.
When identifying the independent and dependent quantities, we think about what would cause the other to change. The score on the test would not cause the number of hours spent studying to change; rather, the number of hours spent studying would cause the score to change. This means that the number of hours studying would be the independent quantity and the score would be the dependent quantity.
Plotting the graph with the time studying on the x-axis (independent) and the score on the y-axis (dependent) gives you the graph shown. You can see in the image that there seems to be a positive correlation; the data seem to generally be heading upward.