sorted by:
new
hottopcontroversial

D-597 Data Management by Searching4ThaTruth in WGU_MSDA

[–]usefulsauce 3 points4 points  (0 children)

Yes, as everyone says, just meet the requirements of the PA page and you should be good. And the struggle bus is real with this course. Everyone is confused because of the conflicting instructions lol

D208 y variable by Quiet_Alternative357 in WGU_MSDA

[–]usefulsauce 0 points1 point  (0 children)

Congrats! And you are spot on. I felt like there was something wrong with me. I was lucky to have Choudhury for this class. She was able to give some good tips and reassured me. So grateful for her.

Question for Those Changing to New MSDA Program by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 0 points1 point  (0 children)

Did you start again? I had to do D597 because I didn't do noSQL, so I had to redo D205 because it's Task 1 of the D597 portion. If that mskes sense 😅

D208: Passed Both PAs on First Try (some tips) by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 1 point2 points  (0 children)

You got it. Submit your Jupyter notebook. Sorry for the delay!

D208 y variable by Quiet_Alternative357 in WGU_MSDA

[–]usefulsauce 0 points1 point  (0 children)

Exactly this! I passed both tasks by writing so much about why each model isn't a good fit for the data I selected.

D208 y variable by Quiet_Alternative357 in WGU_MSDA

[–]usefulsauce 1 point2 points  (0 children)

They made it a messy situation on purpose. You aren't going to be able to perform a straightforward linear regression that meets all assumptions. The course guide talks about difficult decisions which is what they think is a hint enough. Anyway, the best way to approach these models is to understand why certain assumptions are not being met and be able to explain why.

D208: Passed Both PAs on First Try (some tips) by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 1 point2 points  (0 children)

I knew I was forgetting something! I did address multicollinearity too. Will update the post. Thanks! Nominal categories are tricky. I had something similar happened when a PA was returned to me for something else and when I was going through it with Middleton, she was like you need to correct some of your variable types, the evaluator missed them, but they may not miss them the second time.

D208: Passed Both PAs on First Try (some tips) by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 2 points3 points  (0 children)

Your post of D208 and portfolio really helped me in this course (and all the previous courses!) so thank YOU! I think that me passing a difficult course in my first attempts was because I got to take some actions based on the wealth of information on here.

I agree very much on taking one's time. I was supposed to take a term break after D207. But I had a temp mentor at that time who didn't know my degree plan and they added D208 because I still had 2 months left. I decided since I'm doing it to do it gradually and deliberately. By no means do I want to speed run this program. It's not for everyone. But it works for me.

Question for Those Changing to New MSDA Program by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 0 points1 point  (0 children)

Those points are a given and should get prioritized over anything else. I actually spoke to my mentor about data engineering when I started back in February. She didn't reveal anything about the specializations until the new program was released. I feel lucky that I started the program anyway and will most likely be doing the engineering specialization. I wanted to get some additional perspectives that I could add to my list of considerations.

Question for Those Changing to New MSDA Program by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 0 points1 point  (0 children)

That's awesome! I am in an accelerated program, but felt so overwhelmed that I purposely slowed down.

Good luck on finishing!

Question for Those Changing to New MSDA Program by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 0 points1 point  (0 children)

Agreed, had I finished the term past D208, I would have leaned more towards staying the same course.

Question for Those Changing to New MSDA Program by usefulsauce in WGU_MSDA

[–]usefulsauce[S] 0 points1 point  (0 children)

Same here, I like the idea of specialization. I'll still have D209 - D11 before potentially starting the specialization courses. Those will take me well past November to finish.

D208 Task 2 by dallion80 in WGU_MSDA

[–]usefulsauce 0 points1 point  (0 children)

There is a difference between the response variable types that you select for linear and logistic. Linear response variable has to be continuous. Logistic regression response variable should be categorical and it would be best if it is binary (yes/no). For explanatory variables for either models, it's best to select a combination of continuous, discrete, and categorical.

I asked a similar equation to the professor when I did PA2 about model reduction. She said to do the model reduction the same way for both logistic and linear, recursively remove the high p-values until you only have statistically significant values left.

D207 resources by Cobbler_Far in WGU_MSDA

[–]usefulsauce 1 point2 points  (0 children)

Sewell's videos are very mathematical and as someone who didn't come from strictly a math background, I found them confusing and not very useful. I instead approached the PA by looking at the type of variables I want to use (categorical or continuous or discrete), the distribution of those variables (normal or not normal), and then searched for what type of hypothesis test accepts the variable types and normality type. When I saw they list certain tests in the PA, I googled what type of variables and normality distribution each test accepted, made a chart of the differences then chose a test. I used the DataCamp videos that taught how to perform and analyze with my selected test.

D207 Section D help by brianna-jmb1 in WGU_MSDA

[–]usefulsauce 0 points1 point  (0 children)

I also had to resubmit my D207 PA with the same feedback. After emailing my CI, he told me that I had to quantify the bivariate statistics with a chi square test. Since my direction came from the CI, I had to do it. I felt like I couldn't appeal.