Answer:
Step-by-step explanation:
Part A
The common difference is -2 as the sequence decreases down to 2 each. Thus, the sequence is an arithmetic sequence. To find the nth term of an arithmetic sequence, we can follow the formula:
Where is the nth term,
is the first term, and
is the common difference which we know that it is -2. By substitution of values we know, we will have:
Hence, the nth term of the sequence is
Part B
The common difference is -5 as the sequence decreases by 5 each. This also makes the sequence an arithmetic sequence. Thus, we can apply the same formula as we did previously. By substitution of known values, we will have:
Hence, the nth term of the sequence is
The greatest common factor of 14, 56, and 63 is,
⇒ 7
We have to give that,
Numbers are,
14, 56 and 63
Since, The highest number that divides exactly into two more numbers, is called Greatest common factor.
Now, Factors of the numbers are,
14 = 2 x 7
56 = 2 x 2 x 4 x 7
63 = 3 x 3 x 7
Hence, the greatest common factor of 14, 56, and 63 is,
⇒ 7
To learn more about the Greatest common factors visit:
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Answer:
Step-by-step explanation:
The options for this answer are
A. a set of nine data pairs with a correlation coefficient r = –0.4
B. a set of five data pairs with a correlation coefficient r = 0.3
C. a set of four data pairs with a correlation coefficient r = –0.8
D. a set of six data pairs with a correlation coefficient r = 0.6
The correlation coefficient is a statistical measure about the relationship between two variables. Specifically, it tells if there's a positive or negative correlation, and how strong or weak it is.
The interval of a correlation coefficient is from -1 to 1, and the nearer the value gets to zero, the less correlation exist between variables. If the coefficient is near 1, that means there is a strong positive correlation, and if the coefficient is near -1, that means there's a strong negative correlation.
So, in this case, option C shows a correlation coefficient of -0.8, which is the "highest" coefficient among options, this means that it represents the strongest correlation among options.
Therefore, the best data set that fits a linear correlation is C.
y + 13 = 5(x + 2)
y – 2 = 5(x – 13)
y + 2 = 5(x + 13)
Answer:
its b :)
Step-by-step explanation:
i aint ever seen two pretty best friends