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of 30 - 36 % for Bokom followed by Atolesum, Anateem and Amolgoduni with the ranges of 27 - 31, 24 - 27 and 17 - 20 % respectively. It is interesting to note that though age increase reduces the household income, percentage increase with increase in quantity of shea collected per day is higher with age increase. This phenomenon could be explained by the fact that the reduction in income as a result of age increase is less compared with the increase in income as a result of increase in quantity of shea collected per daw

Figure 6 of 30 - 36 % for Bokom followed by Atolesum, Anateem and Amolgoduni with the ranges of 27 - 31, 24 - 27 and 17 - 20 % respectively. It is interesting to note that though age increase reduces the household income, percentage increase with increase in quantity of shea collected per day is higher with age increase. This phenomenon could be explained by the fact that the reduction in income as a result of age increase is less compared with the increase in income as a result of increase in quantity of shea collected per daw

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The methodology had been divided into three sections under the Data Collection and Processing
The methodology had been divided into three sections under the Data Collection and Processing
Table 2: Presents the results of the regression analysis of the final model
Table 2: Presents the results of the regression analysis of the final model
Figure 2: Residual vs. explanatory variables scatter plots Table 3: Comparison of normality test results
Figure 2: Residual vs. explanatory variables scatter plots Table 3: Comparison of normality test results
The histogram and the residual vs. observations plot of Figures 3 and 4 also give a visual representation of the residual distribution. In conclusion it could be said that although the normality of the distribution of the residuals is not perfectly normal, the deviation from normality is within an acceptable range and therefore the residuals of the final regression model of this work could be comfortably termed to be normal and therefore reject the non- normality hypothesis.
The histogram and the residual vs. observations plot of Figures 3 and 4 also give a visual representation of the residual distribution. In conclusion it could be said that although the normality of the distribution of the residuals is not perfectly normal, the deviation from normality is within an acceptable range and therefore the residuals of the final regression model of this work could be comfortably termed to be normal and therefore reject the non- normality hypothesis.
It can also be seen from table 4 that percentage increase in income with 100 % increase in quantity of shea picked per day is higher in the range
It can also be seen from table 4 that percentage increase in income with 100 % increase in quantity of shea picked per day is higher in the range
Table 4: Percentage increase in household income per | % increase in shea collection
Table 4: Percentage increase in household income per | % increase in shea collection
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GeographySocioeconomics
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