First we will find d=A-B
A | B | d |
4.5 | 6.9 | -2.4 |
5.5 | 5.8 | -0.3 |
7.4 | 5.7 | 1.7 |
4.4 | 5.6 | -1.2 |
4.5 | 7 | -2.5 |
Total | -4.7 |
So
Hence answer here is B. -0.94
Data sets A and B are dependent. Find d. A4.5 5.5 7.4 4.4 4.5 B| 6.9...
n the table below, earthquake magnitudes are given for any
region for the last 100 years. Convert each value in this table to
your own values to get a new table.
your new values
A) frequency table and create histogram find
B)standard deviation, find values
C) ,%variation coefficients find values
D) mode and median find values
use the formula below for conversion
Mnew=M-log10(N)
N=33
please show which item you solved when solving
Sample (A B C D)
single digit after...
# 40 please
Question 39 Provide an appropriate response. Data sets A and B are dependent. Find the test statistic. А 6.1 7.1 9.0 6.0 6.1 8.5 7.4 7.3 7.2 8.6 Assume that the paired data came from a population that is normally distributed. B O 1.112 O 1.212 1.321 O - 1.321 Question 40 Provide an appropriate response. Data sets A and B are dependent. Find the test statistic. A 13 11 30 26 14 B 11 7 8...
30. Data sets A and B are dependent . Find the critical value, to, to test the claim that u(d)-0. Use a-0.05. A 40 38 57 53 4 B 38 34 35 45 32 31. Data sets A and B are dependent. Test the claim that the paired sample data is from a population with a mean difference of 0. Use a = 0.05. A 37 35 54 50 38 B 35 31 32 42 29
Data sets A and B are dependent. Find the test statistic.
Assume that the paired data came from a population that is normally
distributed.
QUESTION 7 The data set Beer Large, which can be found in StatCrunch Shared Data Sets, gives the Alcohol, Carbohydrates and Calories for different brands of beer. The explanatory variable is x + Carbohydrates and the response variable is Y - Calories. Use this information to answer: Calculate the correlation between carbohydrates and calories. (4 decimal places) Row vars varo var var 8 var9 var 10 2 الميا ABV 4.1 5.4 4.43 4.13 5.9 4.9 Carbs 2.6 13.7 5.8 5...
The following table shows the inflation rate and unemployment rate, both in percent, for the years 1981-2008. We will investigate some methods for predicting unemployment. 4.4 X (L1) y (L2) Year Inflation Unemployment 1981 8.9 7.6 1982 3.8 9.7 1983 3.8 9.6 1984 3.9 7.5 1985 3.8 7.2 1986 1.1 7 1987 6.2 1988 4.4 5.5 1989 4.6 5.3 1990 6.1 5.6 1991 3.1 6.8 1992 2.9 7.5 1993 2.7 6.9 1994 2.7 6.1 1995 2.5 5.6 1996 5.4 1997...
Age Mem
IQ Reading
Ability
6.7
4.4
95 7.2
5.9
4
90 6
5.5
4.1
105 6
6.2
4.8
98 6.6
6.4
5
106 7
7.3
5.5
100 7.2
5.7
3.6
88 5.3
6.15
5
95 6.4
7.5
5.4
96 6.6
6.9
5
104 7.3
4.1
3.9
108 5
5.5
4.2
90 5.8
6.9
4.5
91 6.6
7.2
5
92 6.8
4
4.2
101 5.6
7.3
5.5
100 7.2
5.9
4
90 6
5.5
4.2
90 5.8
4
4.2
101 ...
Saved 2023 A sample of 100 bank customer waiting times are given in the following table: Waiting Times (in Minutes) for the Bank Custoner Waiting Tine Case 4.5 9.7 11.8 10.4 4.2 7.e 5.5 8.7 8.8 5.1 5.4 4.5 6.2 3.9 8.7 7.6 4.7 4.0 4.0 10.1 .3 2.8 5.4 6.5 9.7 5.2 7.0 5.8 4.5 8.2 1.9 5.2 4.1 7.9 5.3 8.8 6.2 4.1 4.1 4.5 10.4 .2 7.0 6.8 5.5 8.3 11.3 5.9 8.8 2.8 6.7 5.5 5.e...
The data on the below shows the number of hours a particular drug is in the system of 200 females. Develop a histogram of this data according to the following intervals: Follow the directions. Test the hypothesis that these data are distributed exponentially. Determine the test statistic. Round to two decimal places. (sort the data first) [0, 3) [3, 6) [6, 9) [9, 12) [12, 18) [18, 24) [24, infinity) 34.7 11.8 10 7.8 2.8 20 9.8 20.4 1.2 7.2...
11.38 Building a multiple linear regression model. Let’s now build a model to predict the life-satisfaction score, LSI. (a) Consider a simple linear regression using GINI as the explanatory variable. Run the regression and summarize the results. Be sure to check assumptions. (b) Now consider a model using GINI and LIFE. Run the multiple regression and summarize the results. Again be sure to check assumptions. (c) Now consider a model using GINI, LIFE, and DEMOCRACY. Run the multiple regression and...