We are given that a national study report indicated that 20.9% of Americans were identified as having medical bill financial issues.
A news organization randomly sampled 400 Americans from 10 cities and found that 90 reported having such difficulty.
<u><em>Let p = proportion of Americans who were identified as having medical bill financial issues in 10 cities.</em></u>
SO, Null Hypothesis, : p 20.9% {means that % of Americans who were identified as having medical bill financial issues in these 10 cities is less than or equal to 20.9%}
Alternate Hypothesis, : p > 20.9% {means that % of Americans who were identified as having medical bill financial issues in these 10 cities is more than 20.9% and is more severe}
The test statistics that will be used here is <u>One-sample z proportion</u> <u>statistics</u>;
T.S. = ~ N(0,1)
where, = sample proportion of 400 Americans from 10 cities who were found having such difficulty = = 0.225 or 22.5%
n = sample of Americans = 400
So, <u><em>test statistics</em></u> =
= 0.77
<u></u>
<u>Now, P-value of the test statistics is given by the following formula;</u>
The number of cells in a tile is 4. If colored alternately, there are 3 of one color and 1 of the alternate color. To balance the coloring, an even number of tiles is needed. Hence the board dimensions must be multiples of 4.
The correlation coefficient is a measure of the strength of the linear relationship between two variables and is denoted by r. Values between 0.3 and 0.7 indicate a moderate positive (negative) linear relationship .
Values between -0.3 and -0.7 indicate a moderate negative linear relationship .
The only value of r in the option is r= -0.64 lies in given interval of moderate negative linear relationship .