Would like to understand the relationship between variables and predict "Avg Latency"
Sample Data - [login to view URL]
Dependent Var: avg_latency (Trying to predict)
Independent Vars (Continuous): read_ops, write_ops, other_ops, read_MB, write_MB, read_latency, write_latency, other_latency
Independent Vars (Categorical): Timestamp, uniq_vol
On the time variable, you can convert this to a quantitative variable. If you wanted to look at day of week, you could assign numeric values like Sunday=1, Monday=2, etc. And same for hour, you could use the 24 hour clock to assign a numeric value to each hour to include this as a variable in your model.
On the uniq_vol variable, this is a bit more complicated. Probably the best way (but very time consuming) would be to create a variable for each possible value and then assign 0 or 1 to each of those variables where for each data point, you would give a value of 1 to the uniq_vol category that data point has and then assign 0 to all the other category variables.
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Hey, I will do multiple linear regression for you. It's simple by creating dummy variables for categorical features. Please award me the bid to get the delivery by today. Thanks and regards, Arka
As an engineer in statistics and applied economics and specialized in Microsoft Office (MOS Diploma), I am able, available and ready to do this work on time, I can show you an example for calibration