CT 60, 894 |
NY 1,029,888 |
MO 245,425 |
MS 92,831 |
CO 251,595 |
ME 60,894 |
PA 573,815 |
NE 80,432 |
NC 370,883 |
ID 64,514 |
MA 380, 277 |
IL 574,429 |
ND 36,863 |
SC 176,365 |
MT 45,359 |
NH 70,699 |
IN 252,150 |
SD 38,950 |
TN 246,025 |
UT 119, 240 |
RI 47.731 |
MI 407,475 |
AL 165, 716 |
VA 384,479 |
WY 25,707 |
VT 31,284 |
OH 477, 536 |
AR 102,755 |
WV 65,138 |
AK 37,053 |
DE 42.655 |
WI 246,818 |
FL 876,422 |
AZ 257,505 |
CA 1,858,421 |
DC 44,361 |
IA 122,914 |
GA 383,834 |
NM 75,977 |
HI 69,262 |
MD 282, 921 |
KS 11,339 |
KY 157,066 |
OK 136,037 |
NV 125,801 |
NJ 469,735 |
MN 266,161 |
LA 168,245 |
TX 1,120,665 |
OR 179,015 |
WA 350,959 |
What is the confidence interval of 97%? What is the margin of error? Please show your work.
using excel we have
Confidence Interval Estimate for the Mean | ||
formula used | ||
Data | ||
Sample Standard Deviation | 331713.9889 | STDEV.S(A2:A53) |
Sample Mean | 268055.3846 | AVERAGE(A2:A53) |
Sample Size | 52 | COUNT(A2:A53) |
Confidence Level | 97% | |
Intermediate Calculations | ||
Standard Error of the Mean | 46000.45369 | C4/SQRT(C6) |
Degrees of Freedom | 51 | C6-1 |
t Value | 2.2325 | T.INV.2T(1-C7, C11) |
Margin of Error | 102696.1653 | C12*C10 |
Confidence Interval | ||
Interval Lower Limit | 165359.22 | C5-C13 |
Interval Upper Limit | 370751.55 | C5+C13 |
the confidence interval of 97% is (165359.22,370751.55)
the margin of error is 102696.1653
CT 60, 894 NY 1,029,888 MO 245,425 MS 92,831 CO 251,595 ME 60,894 PA 573,815 NE...
and MT NE NV ND NH NJ NM NY NC OH OK OR PA RI SC SD TN TX UT VA VT WA WV WI WY EM 95813624 7262 1430278 3 22896 03171 12111 1165380 2111211 1.0160 72221 8 tat-AL AK AZ CA CO CN DE DC FL GA HI ID IL IN IA KA KY LA ME MD MA MI MN MS MO ONEC EDA-NSO git M w w M w w E E E E E W W...
Question 2: How do the average credit scores of people living in various cities in the US differ? The file Credit Score Data of 143 American cities is provided in Canvas. Construct a histogram Create a Five Summary Report Calculate Mean, Variance and Standard Deviation What conclusion can you reach concerning the average credit scores of people living in different American cities? City State Average Credit Score Detroit Mi 743 New York NY 762 Minneapolis MN 787 Hartford CT 774...
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CPS 276 DOC02-- Assignment 02 Cost of Living Calculator Your client maintains job search website. As a service on their website, they need an application that compares costs of living between different metropolitan areas. Client will pay $780 for a complete application. Background Information: A person living in an area with a high cost of living will need higher income to maintain the same standard of living as someone living in an area with a low cost of living. For...
An article reported the estimated percentage of households with only wireless phone service (no land line) for the 50 U.S. states and the District of Columbia. In the accompanying data table, each state was also classified into one of three geographical regions—West (W), Middle states (M), and East (E). Wireless % Region State Wireless % Region State 14.9 M AL 10.2 W MT 12.7 W AK 23.2 M NE 19.9 W AZ 10.8 W NV 23.6 M AR 16.9 M...
We consider the multiple linear regression with LIFE (y) as the response variable, and MALE, BIRTH, DIVO , BEDS, EDUC, and INCO, as predictors. QUESTION: Plot the standardized residuals against the fitted values. Are there any notable points. In particular look for points with large residuals or that may be influential. # please screenshot the Rcode for the plot. # data information are as follows: "STATE" "MALE" "BIRTH" "DIVO" "BEDS" "EDUC" "INCO" "LIFE" AK 119.1 24.8 5.6 603.3 14.1 4638...
Census data was collected on the 50 states and Washington, D.C. We are interested in determining whether average lifespan (LIFE) is related to the ratio of males to females in percent (MALE), birth rate per 1,000 people (BIRTH), divorce rate per 1,000 people (DIVO), number of hospital beds per 100,000 people (BEDS), percentage of population 25 years or older having completed 16 years of school (EDUC) and per capita income (INCO). A MLR model has LIFE (y) as the response...
We consider a multiple linear regression model with LIFE (y) as the response variable, and MALE (x1), BIRTH (x2), DIVO (x3), BEDS (x4), EDUC (x5), and INCO (x6), as predictors. "STATE" "MALE" "BIRTH" "DIVO" "BEDS" "EDUC" "INCO" "LIFE" AK 119.1 24.8 5.6 603.3 14.1 4638 69.31 AL 93.3 19.4 4.4 840.9 7.8 2892 69.05 AR 94.1 18.5 4.8 569.6 6.7 2791 70.66 AZ 96.8 21.2 7.2 536.0 12.6 3614 70.55 CA 96.8 18.2 5.7 649.5 13.4 4423 71.71 CO 97.5...
College Graduation and Other State Characteristics (n = 50, k = 8) omit State ColGrad% Dropout EdSpend Metro% Age LPRFem Neast Seast West Midwest AL 19.8 19.1 1221 89.2 37.4 55.8 0 1 0 0 AK 28.7 8.3 2187 74.7 33.9 65.6 0 0 1 0 AZ 27.9 14.3 1137 96.7 34.5 57.4 0 0 1 0 AR 17.5 18.6 1158 78.8 37.0 54.9 0 1 0 0 CA 30.4 19.7 1657 99.3 34.4 57.6 0 0 1 0 CO...