I am curious on how to solve this problem without using SPSS. Unfortunately, SPSS is not working on my computer right now. Is there another way to solve this problem?

A biologist is studying the levels of heavy metal contaminants among a population of the South Nakaratuan Chubby Bat. The biologist is interested in constructing a simple linear regression model to investigate the relationship between weight of an animal and the level of heavy metal contamination. In the proposed regression model the level of contaminant is the response variable and weight is the explanatory variable. The contaminant level is measured in parts per billion (ppb) and weight in grams. A random sample of 20 individuals is selected and measurements are taken. Contaminant study in South Nakaratuan Chubby Bat Download the data Contaminant level Weight [ppb) (g) 132 107 163 135 155 130 165 143 169 127 149 111 151 135 129 114 158 131 112 103 116 104 119 108 111 109 122 102 144 127 148 118 108 101 153 129 188 140 214 101 Plotting the data, the researcher notices an obvious outlier. They decide to do the regression analysis with and without the outlier and compare the results Calculate the slope (b1) and intercept (bo) of the simple regression equation using the data provided. Give your answers to 2 decimal places. a) Slope = b1 = b) Intercept = bo = Find the proportion of variation in the values of contaminant level that is explained by the regression model. Give your answer as a decimal to 2 decimal places. c) R2- Repeat this process omitting the outlier: d) Slope = b1 = e) Intercept = bo = Find the proportion of variation in the values of contaminant level that is explained by the regression model. Give your answer as a decimal to 2 decimal places. f) R2