a) The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. As such, he is interested in investigating the association between the age of the respondents and their knowledge level. Table 2 below shows the knowledge level of respondents, by age group. Table 2 Age Group Knowledge Level Total Poor Satisfactory Good 18 - 25 33 16 13 62 26 - 34 30 18 12 60 35 - 44 29 14 12 55 45 - 54 36 16 18 70 55 - 75 17 14 22 53 Total 145 78 77 300 Conduct a test, at the 5% level of significance, to determine whether the data provided sufficient evidence to conclude that an association exists between age group and knowledge level. (i) State the hypotheses to be tested: H0: H1: Calculate: (ii) state the degrees of freedom for this test (iii) the p-value for this test, given that the chi-square test statistic, c2, is 11.029. (iv) state the conclusion for the test. Give reason for your answer. (b) Finally, the researcher is interested in examining the regression model for knowledge, attitude and practices towards the COFLU-20. The following model was developed to forecast individual practices towards COFLU-20 using knowledge and attitude scores. P = α + β K + δ A where P = Practice towards COFLU-20 score K = Knowledge towards COFLU-20 score A = Attitude towards COFLU-20 score The data are processed using MINITAB and the output in Exhibit 1 below was obtained: Exhibit 1 The regression equation is ************* Predictor Coef SE t-ratio P Constant 4.755 0.462 10.282 0 Knowledge 0.8 0.039 2.055 0.041 Attitude 0.024 0.6 0.393 0.695 R-sq = 81.5% Analysis of Variance SOURCE DF SS MS F P Regression 2 38.06 19.03 2.284 0.104 Error 297 2474.887 8.333 Total 299 2512.947 (i) Identify the dependent variable(s) and the independent variable(s). (ii) Is δ significant? Show proof of the testing process used to arrive at your decision. State what this means in terms of attitude and practices. (iii) What does the value of R-sq indicate? Comment on the value of R-sq.
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
a) The researcher is concerned that older persons may not be knowledgeable of the COFLU-20. As such, he is interested in investigating the association between the age of the respondents and their knowledge level. Table 2 below shows the knowledge level of respondents, by age group.
Table 2
|
Age Group |
Knowledge Level |
Total |
|||
|
Poor |
Satisfactory |
Good |
|||
|
|
18 - 25 |
33 |
16 |
13 |
62 |
|
26 - 34 |
30 |
18 |
12 |
60 |
|
|
35 - 44 |
29 |
14 |
12 |
55 |
|
|
45 - 54 |
36 |
16 |
18 |
70 |
|
|
55 - 75 |
17 |
14 |
22 |
53 |
|
|
Total |
145 |
78 |
77 |
300 |
Conduct a test, at the 5% level of significance, to determine whether the data provided sufficient evidence to conclude that an association exists between age group and knowledge level.
(i) State the hypotheses to be tested:
H0:
H1:
Calculate:
(ii) state the degrees of freedom for this test
(iii) the p-value for this test, given that the chi-square test statistic, c2, is 11.029.
(iv) state the conclusion for the test. Give reason for your answer.
(b) Finally, the researcher is interested in examining the regression model for knowledge, attitude and practices towards the COFLU-20. The following model was developed to forecast individual practices towards COFLU-20 using knowledge and attitude scores.
P = α + β K + δ A
where P = Practice towards COFLU-20 score
K = Knowledge towards COFLU-20 score
A = Attitude towards COFLU-20 score
The data are processed using MINITAB and the output in Exhibit 1 below was obtained:
Exhibit 1
The regression equation is *************
|
Predictor |
Coef |
SE |
t-ratio |
P |
|
Constant |
4.755 |
0.462 |
10.282 |
0 |
|
Knowledge |
0.8 |
0.039 |
2.055 |
0.041 |
|
Attitude |
0.024 |
0.6 |
0.393 |
0.695 |
R-sq = 81.5%
|
Analysis of Variance |
|||||
|
SOURCE |
DF |
SS |
MS |
F |
P |
|
Regression |
2 |
38.06 |
19.03 |
2.284 |
0.104 |
|
Error |
297 |
2474.887 |
8.333 |
||
|
Total |
299 |
2512.947 |
(i) Identify the dependent variable(s) and the independent variable(s).
(ii) Is δ significant?
Show proof of the testing process used to arrive at your decision.
State what this means in terms of attitude and practices.
(iii) What does the value of R-sq indicate? Comment on the value of R-sq.
Step by step
Solved in 4 steps with 4 images
