Answer:
Individuals end to continue paying the premiums of the automobile insurance as a habit. However, serious thoughts and putting in element of strategizing helps to reduce the premium in most cases. At times, there is a sudden like on the part of the insurer even for a flawless driver.
A good look up and research of the insurance websites can be of real help in comparing whether a better deal is offered by the other insurance companies, or whether a certain change in the policy or small adjustments of the term would give benefit to the customer.
In case a speeding ticket is received, or an accident is mentioned in the driving history, it is maintained there in for a period of three to five years. Thus, the premium increases substantially. A change of insurer is advised in such situations, where a major search for an insurer, who does not pay that much importance to these details, is to be carried on.
Again, having a teenager driver in the family calls for a caution as the insurance premium increases drastically in such occasion. Having clean driving record of the parents, or kids commuting to far away schools without cars help in such situation.
Answer: x=7
Step-by-step explanation:
3x=21
21 divided by 3 is 7
so x equals 7
14/2.99=1/x
14x=2.99(1)
x=2.99/14
x=0.213571429
Answer/Step-by-step explanation:
To represent the data given on a stem and leaf plot, the whole number in a given value would be used as the stem, while the number after the decimal point is the leaf. (Key: 3|3 = 3.3).
For example, in the first stem in the first row, we have 4 as the stem. All values that starts with 4 point would be represented in this row. The digit after 4 point for each of the values would be written on the leaf column in the first row, from the least to the largest. For the first row we have: 4 | 3 9.
Same applies to the rest rows.
The stem plot would look like the one below:
Ice Thickness:
Stem | Leaf
4 | 3 9
5 | 1 8 8 8 9
6 | 5 8 9 9
7 | 0 2 2 2 2 5 9
8 | 0 7
The data of the stem-and-leaf plot shows a bell-shaped pattern with majority of the ice thickness for the 20 locations clustering around the center of the data distribution.
