4. In an experiment there were Nexp values measured. The expected values based on similar measurements are known. Both sets are presented in the Table of data. The question that arose was whether the differences between the observed and expected data are due to chance. Use the chi-square test to determine the probability that the differences arose from chance.
|
Data |
||
|
Index |
Observed |
Expected |
|
1 |
8.00 |
6.40 |
|
2 |
10.00 |
13.60 |
|
3 |
16.00 |
13.00 |
|
4 |
7.00 |
9.00 |
|
5 |
13.00 |
10.00 |
|
6 |
11.00 |
12.00 |
|
7 |
6.00 |
8.00 |
|
8 |
7.60 |
6.40 |
|
Nexp |
8 |
|
Ho:there is no significant difference between the expected and observed result
H1:there is a significant difference between the expected and observed result
| Index | Observed | Expected | (O-E)²/E |
| 1 | 8 | 6.4 | 0.4 |
| 2 | 10 | 13.6 | 0.952941176 |
| 3 | 16 | 13 | 0.692307692 |
| 4 | 7 | 9 | 0.444444444 |
| 5 | 13 | 10 | 0.9 |
| 6 | 11 | 12 | 0.083333333 |
| 7 | 6 | 8 | 0.5 |
| 8 | 7.6 | 6.4 | 0.225 |
| total | 4.1980266 |
chi square statistic = Σ(O-E)²/E=
4.198
degree of freedom = n-1 = 7
p-value = 0.7567
p-value >α=0.05
so, there is no significant difference between the expected and observed result
4. In an experiment there were Nexp values measured. The expected values based on similar measurements...
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