Your question is lacking the necessary answer options, so I will be adding them here:
A. standard deviation.
B. mean.
C. median.
D. correlation coefficient.
E. range.
So, given your question, the statistical measure which is most helpful for indicating the extent to which high school grades predict college grades is: D. correlation coefficient.
A statistical measure can be defined as a numerical measurement of each value of a quantitative variable in a given population. Some of the commonly used statistical measure in science include the following;
Correlation coefficient can be defined as a statistical measure used for the measurement of the strength of the relationship between two (2) known variables and to represent their linear interdependence. Thus, the values of a correlation coefficient typically range from +1 (strong positive relationship) to -1 (strong negative relationship)
Hence, correlation coefficient is a statistical measure which is most helpful for indicating the extent to which high school grades predict college grades because it would determine the strength of the relationship between them.
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I believe the answer would be
L. l
Top- L LL, Ll,
Bottom- l Ll, ll.
Explanation:
<h2>It is interesting to note that CO2 is still believed to be the No 1 greenhouse gas instead of water vapour. Many excellent climate scientist (e.g. Richard Lindzen, Roy Spencer, John Christy, etc) have dealt with the issue and shown both in books and research articles that CO2 is a very minor player governing global climate.</h2><h2>So what drives climate?</h2><h2>The answer must obviously be found in the hydrological cycle, where the oceans play a major role together with extraterrestrial process with the Sun having the ultimate role. We know that solar energy (insolation) does not vary sufficiently to explain the climatic excursion our planet has experienced on a short and long term. It is sufficient to consider the Little Ice Age and the Medieval Warm Period, not mentioning the past ice ages, to understand that there are many complicated factors to consider before we can explain climate variability.</h2><h2>Solar activity is naturally a major player but this does not mean only total solar insolation (TSI) but also solar magnetic activity. Also the gravitational influence of the entire solar system must be taken in account, not forgetting our own natural satellite, the Moon, influencing at least ocean tides. Very interesting views on climate variability and cosmic activity have been presented by Henrik Svensmark.</h2><h2>A very simplistic example how the water cycle could adjust climate is the following mental construct: The Sun warms the ocean surface increasing evaporation. Increase in water vapour content decreases the density of the air, which thus rises to higher altitudes where eventually adiabatic cooling reaches a level where water vapour starts to condense. The availability of condensation nuclei, possibly enhanced by high energy cosmic radiation especially during low level solar magnetic activity, leads to strong cloud formation. This eventually limits solar warming of the ocean surface and decreases evaporation with less cloud formation. This entire cycle can be compared to a very effective thermostat, by some aptly termed the water thermostat responsible for keeping global temperatures at a suitable level depending on local conditions</h2>
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Answer:
The object's velocity is increasing
Explanation:
From the graph above, we can deduce that the velocity is increasing. From the first stage, v=m/s=0.
At the third stage, v=20/2= 10m/s.
At the 5th stage, v=80/4=20m/s.
This shows velocity is increasing.
