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d.  What percent of females have a graduation degree?
                     Ans.  37/282 = 13.12%
                       4.   Find the Pearson’s coefficient of correlation between farmer education and yearly farm yield from the following
                          data:

                                    No. of years of farmer education   0     2    4     6     8    10

                                    Yield per year                     4     4    6     10    9    7

                     Ans.      x         y         xy        x 2        y 2
                               0         4          0         0        16

                               2         4          8         4        16
                               4         6         24        16        36
                               6        10         60        36       100
                               8         9         72        64        81
                              10         7         70       100        49
                                                                       2
                             Σx=30     Σy=40    Σxy=234    Σx =220   Σy =298
                                                             2
                          N = No. of samples = 6
                                     N Σxy − (Σx) (Σy)
                          r =
                                     2
                                 N Σx  − (Σx) ][NΣy  – (Σy) ]
                                                  2
                                                       2
                                            2
                                  6(234) – (30) (40)         204
                                                          =        = 0.72
                                         2
                                                      2
                              6(220) – (30)  (6(298) – (40) )  280.99
                       5.  Define the following terms and give examples from real life:
                          a.   Positive Correlation
                          b.   Causation
                          c.   Negative Correlation
                          d.   Outlier
                     Ans.  a.     Positive Correlation: Positive correlation is the relationship between two variables, in which both variables
                               have a linear relationship. As one variable increases/decreases, the second variable too increases/decreases.
                               For example, when fuel prices increase, prices of airline tickets also increase.
                          b.     Causation: Causation shows that an event is the direct result of the occurrence of another event, i.e. a causal
                               relationship exists between the two events. This is also called cause and effect. For example, a speeding car
                               leads to an accident. The accident is due to causation.

                          c.     Negative  Correlation:  Negative  correlation  is  the  relationship  between  two  variables,  where  one  variable
                               increases as the second variable decreases, and vice versa. For example, more exercising leads to a decrease
                               in body weight.
                          d.     Outlier: In statistics, outliers are data points that are significantly different from other observations. Outliers
                               may  be  due  to  measurement  irregularity  or  may  indicate  experimental  error;  the  latter  are  sometimes
                               excluded from the data set. Outliers can cause serious problems in statistical analysis.
                 C.   Competency-based/Application-based questions:

                       The following question consist of two statements: Assertion (A) and Reason (R).
                     Assertion (A): The dependent variable is the variable under study, and it is the variable that the regression model tries
                     to predict.



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