The Chi-Square Test TABLE2 Table of x2Values Reject Accept .10 .05 .01 .50 .30 d
ID: 200067 • Letter: T
Question
The Chi-Square Test TABLE2 Table of x2Values Reject Accept .10 .05 .01 .50 .30 df p=.99 .95 .90 .80 .70 148 455 1.074 2.706 3.841 6.635 713 1.386 2.408 4.605 5.991 9.210 -3.6656.251) 7.816 11.345 4.878 7.779 9.488 13.27 3 6.064 9.236 11.070 15.086 1 1 000157 003930158 0642 352 584 1.005 1.424 711 1.064 1.649 2.195 3.3 3 115 554 1.145 1.610 2.343 3.000 646 2.733 3.490 4594 5.527 7.344 9.524 13.362 15.507 20.090 4 297 08721.635 2.204 3070 3.828 5.348 7.231 10.645 12.592 16.812 2167 2.833 3.822 4.671 6.346 8.383 12.017 14.067 18.475 8 1. 2.088 3.325 4.168 5.380 633 8.343 10.656 14.684 16.919 21.666 3940 4865 6.179 7.267 9.342 11.781 15.987 18.307 23.209 10 2.558 " Selected data from R. A. Pisher and E Yates, Statistical tables for biological, agricultural and medical research London: Oliver and Boyd, 1943). A x value of 3.841 for a two-term ratio corresponds to a probability of 1 in 20, or 05. One would i alu ahnut 5% of similar trials if the hypothExplanation / Answer
Keep all the solved problems as well as X2 value table with you before reading the answer. Just follow the answer step by step and keep comparing it with the data you have. Do not read the entire answer at first, you might get even more confused. Just follow the instructions line by line and you will get it. This is pretty easy problem from Biostat.
1. X2 test, it is called as Chi-square test. It is used to check the given data, to check whether the given data suits the pattern mentioned in the standard data.
2. For that purpose we need to arrange the data in the certain way in the table. First column represents the total list of the items we need to examine.
3. Second column is Observed value (o). It will contain the given values in the problem. You can compare this column from various solved examples with the data given in the question to understand it.
4. Next column is Expected Value (E). This value you need to calculate as per the mentioned ratio of the item from the question. e.g. If question says: There are 20 students in the class, and see if it has 50% boys. then your expected number of boys will be 10, regardless what number of boys is given in the problem.
5. REMEMBER THAT: You will never get the expected value from the problem. It is something that you always have to calculate. Numbers given in the problem always fall in Observed data column.
6. When you will be done with these two colomns then calculating further is pretty easy. Next colomn says (O - E). So, just substract value from the cell 'E' from respective 'O' cell.
7. In the next column, just make square of the value you have got in the cell (O-E). At he end of this column you have to make grand total of it.
8. The value obtained by the addition of the values of last colomn is the value of X2. But that is not the answer of the question. It is just a value, which will help you to findout the answer.
9. Now you need to find the value of 'degree of freedom' (D.F.). Just count the number of rows you have in the table excluding the Total row. The degree of freedom will always be one less than that. e.g. if you have 5 rows in the table, D.F. will be 4.
10. Now, check the Table 2: Table of X2 values. In that check the column with title'0.05'. It means percent error, indicated as 'p'.
11. So, we will be calculating the answer for 5% error of the data. Find your D.F. Value in the frist column and find the value in the row for 0.05 error. e.g. for d.f. 2, 0.05 value is : 5.991.
12. When you get this value, compare it with X2 value from the table.
13. If the calculated value is 'Greater than' the tabulated value, the hypothesis will be Rejected.
14. If the calculated value is 'Less than' the table value, the hypothesis will be ACCEPTED.
15. Remember: Nobody asks what is the value of X2 as an answer. It is your responce to it, i.e. Accepted / Rejected.