You would need at least 169 samples (with 95% confidence and with 5%- Margin of error) which is a most common requirement. With your current sample size you are having 11.3% margin of error (with 95% ...

In Minitab, there is no option to restrict the forecasts to positive using ARIMA. Probably you need to consider doing log transformation before forecast and back transform after that as mentioned in ...

Using SMA(1) there is no option to restrict like the way you want. You may want to take the log of the variable to avoid negative values and do the forecasts, and back-transform Please see here for ...

We can not graph both the CI graphs simultaneously because there is no option for that (in regression analysis) using Minitab.

Variance inflation factors (VIF) measure how much the variance of the estimated regression coefficients are inflated as compared to when the predictor variables are not linearly related. It is used ...

The data sets in the following sites are available for free. These data sets have been used to teach ML algorithms to students because for most there are descriptions with the data sets. Also, it's ...

This plot called as "Tree plot" in tableau. You can see here to know how to do that. You can find trail version of Tableau here Hope this helps !

On the X axis, Click and drag on an axis to rescale it. Alternatively, hover over the axis until you see a hand. Then, double-click on the axis and set the parameters in the Axis Specification window. ...

You need to use the EXP() to convert the logs odds to odds. Example: EXP(-1.30) = 0.27 then EXP(logs odds)/(1+EXP(logs odds)) i.e. Probability = (0.27)/(1+0.27) = 0.21 To see how to use EXP in ...

In 'Responses' you need to use the BMI as it is your interest of study. I'm not sure, how you coded Time as 1,2,3 but if it is a factor that affects the response (BMI) then it's okay to use. You may ...

Yes, it is possible to classify more than two classes using Multiclass Kernel-based Vector Machines. This paper explains well about this. There are non-linear separations as well like radial and ...

Recent comparison from DataCamp provides clear picture about R and Python. The usage of these two languages in the data analysis field. Python is generally used when the data analysis tasks need to ...

I believe you know how to check whether the data is stationary or not by looking at the ACF & PACF plots. To do this in Minitab, we use Stat - Time Series - Autocorrelation and Stat - Time Series ...

The Average is a good measure when a dataset contains values that are relatively evenly spread with exceptionally NO high or low values. You can use 'Median' if you find extreme values in your ...

The Answer is YES, you can do. All you need to do is arrange the data in proper manner and know how to feed in the data as required. You can use "Data Analysis" option in Excel. Also, there is an add-...

The interpretation of the output is given below: B - This is the coefficient for the constant (also called the "intercept") in the model. S.E. - This is the standard error around the coefficient for ...

Another method is SVM (Support vector Machines). The classifier function constructed during the training completely decides the differences in data between the classes. We can do this using SAS/R/...

Two series of measurements can be given in two separate columns as well in Minitab. Considering the example in Wiki Enter two samples in two columns Go to Stat Menu -> Basic statistics -> 2-sample-t-...

You can choose the suitable technique after checking the following assumptions with your data Assumptions ------------- Discriminant Analysis ---- Logistic Regression Multivariate Normality -> ...

Follow the below given steps to get the forecast values in Minitab. Go to Stat Menu -> Time series -> ARIMA Input your time series data in "Series" and enter the appropriate order for AR,I and MA. ...

Let us take this example. Three parts were selected that represent the expected range of the process variation. Three operators measured the three parts, three times per part, in a random order. ...

I'm assuming that you are asking about Multiple regression method and Response surface method. Below is the simple explanation about both methods and their applications. As you read through, you will ...

One possible method is SVM (Support vector Machines), it needs a decent amount of data to train the model. The classifier function constructed during the training completely decides the differences in ...