Exam DA0-001 topic 1 question 3 discussion

D. Normalize the variables. Normalization involves transforming the values of the variables so that they have the same scale and range, typically from 0 to 1. This allows the analyst to ensure that each variable has the same weight in the calculation, since all the values are on the same scale. Normalizing the variables will also make it easier to interpret the results and compare the scores of different customers. This is important in creating a likely-to-buy score because it ensures that all three variables have an equal impact on the final score, rather than one variable having a larger weight due to its scale or range.

If you didnt normalise the data you could rank it and then take the average, which would be similar to recoding. However any statistician would normalise the data

normalization of values definitely, depending on the normalization algorithm it may not be a range between 0 to 1, but all values will definitely fit small interval and have same weight/scale

D. Normalize the variables. Normalization involves transforming the values of the variables so that they have the same scale and range, typically from 0 to 1. This allows the analyst to ensure that each variable has the same weight in the calculation, since all the values are on the same scale. Normalizing the variables will also make it easier to interpret the results and compare the scores of different customers. This is important in creating a likely-to-buy score because it ensures that all three variables have an equal impact on the final score, rather than one variable having a larger weight due to its scale or range.

D. Normalize the variables. Normalization is the process of scaling a variable to have a values between 0 and 1. This can be done by subtracting the minimum value of the variable from all the values, and then dividing the resulting values by the range (i.e., the difference between the maximum and minimum values). Normalizing the variables ensures that they all have the same weight in the score calculation, since they are all on the same scale. The other options would not have the same effect. Recoding the variables would involve changing the values of the variables in some way, which would not necessarily give them the same weight. Calculating percentiles or standard deviations would not change the scale of the variables and therefore would not give them the same weight.