MENU
What are you doing if you succumb to "overgeneralization" when analyzing data from metrics?
Suggested Answer: D
Get Premium CIPM Questions
as Interactive Web-Based Practice Test or PDF
Real Exam Format
Detailed Explanations
Instant Access
Get Your Practice Test
The first step to mitigate further risks when a systems audit uncovers a shared drive folder containing sensitive employee data with no access controls is to restrict access to the folder. This can be done by implementing appropriate access controls, such as user authentication, role-based access, and permissions, to ensure that only authorized individuals can view and access the sensitive data.
https://www.sans.org/cyber-security-summit/archives/file/summit-archive-1492158151.pdf
https://www.itgovernance.co.uk/blog/5-reasons-why-employees-dont-report-data-breaches/
41 comments · newest first
FR
Fredric
12 months ago
I don't know, this feels a bit oversimplified.
TA
Tammara
1 year ago
B is also a possibility, but C really nails it.
SA
Salena
1 year ago
Wait, are we sure it's not A? Seems too broad too!
LA
Laurena
1 year ago
Totally agree, C is spot on!
MI
Miesha
1 year ago
Overgeneralization means using limited data to support broad conclusions.
KI
Kizzy
1 year ago
I’m leaning towards A because it makes sense that broad data wouldn’t capture specific meanings, but I could be wrong.
AN
Anglea
1 year ago
I feel like overgeneralization could also relate to having too many types of data, but that seems more like B. I’m confused!
TE
Terina
1 year ago
I remember practicing a question like this, and I think overgeneralization is about using limited data to make broad conclusions, which sounds like C.
AL
Alease
1 year ago
I think overgeneralization means using too broad data, so maybe it's A? But I'm not entirely sure.
MA
Marylou
1 year ago
Okay, let me see here. Present value is about the current worth of a future amount of money or stream of cash flows, discounted at an appropriate interest rate. So I think the best answer is C, that makes the most sense to me.
SA
Salley
1 year ago
Okay, I think I've got this. The key is understanding that the neutral line needs to be grounded at multiple points, not just the power transformer. I'll go with True on this one.
RO
Roxane
1 year ago
I remember discussing Optimal Gateway Routing in class, but I don't think it addresses the root issue here. Maybe it's more about location instead of gateway optimization?
MA
Malcolm
1 year ago
I'm surprised the answer isn't 'E) All of the above'. That's usually the case with these tricky exam questions!
WI
Willard
1 year ago
D) Trying to use several measurements to gauge one aspect of a program.
RA
Raymon
1 year ago
C) Using limited data in an attempt to support broad conclusions.
ME
Merilyn
1 year ago
A) Using data that is too broad to capture specific meanings.
EL
Ellen
2 years ago
Hah, I almost picked B. 'Possessing too many types of data' - that's a new one! Gotta watch out for that data overload.
TA
Tawna
1 year ago
Yeah, it's important to strike a balance and not go to extremes with data analysis.
EL
Eliz
1 year ago
C) Using limited data in an attempt to support broad conclusions.
DO
Dominic
1 year ago
A) Using data that is too broad to capture specific meanings.
LE
Lemuel
2 years ago
I was gonna go with D, but now I'm not so sure. Overgeneralization can definitely happen when you try to measure too many things at once.
JE
Jeniffer
1 year ago
I agree, it's important to have a balance and not go to extremes.
KA
Karl
1 year ago
C) Using limited data in an attempt to support broad conclusions.
LA
Latosha
1 year ago
A) Using data that is too broad to capture specific meanings.
SH
Shawnda
2 years ago
Hmm, I was leaning towards A, but C makes a lot of sense too. Gotta be careful not to draw big conclusions from a small data set.
BL
Blossom
1 year ago
User 4: It's definitely crucial to be cautious when drawing conclusions from a small data set. Both A and C highlight the risks of overgeneralization.
ST
Stefan
1 year ago
User 3: I was also thinking A, but after hearing your points, C seems like a valid choice too.
EV
Evan
1 year ago
User 2: I agree with you, Evan. Using limited data to support broad conclusions can lead to overgeneralization.
NA
Nakita
1 year ago
User 1: I think A is the right answer. It's important to avoid using data that is too broad.
FR
Franchesca
1 year ago
D) Trying to use several measurements to gauge one aspect of a program.
MI
Mireya
1 year ago
Yeah, it's important to strike a balance between the two.
RO
Roselle
1 year ago
C) Using limited data in an attempt to support broad conclusions.
AN
Antonio
1 year ago
A) Using data that is too broad to capture specific meanings.
DE
Dell
2 years ago
I think C is the correct answer. Overgeneralizing from limited data is a common mistake in data analysis.
LO
Lonny
1 year ago
Using too little data can definitely skew our analysis results.
HA
Han
1 year ago
I think C is the correct answer too. We need to be cautious of overgeneralizing.
RO
Rosalyn
2 years ago
It's important to ensure we have enough data to draw meaningful insights.
NA
Narcisa
2 years ago
I agree, using limited data to support broad conclusions can lead to inaccurate analysis.
CA
Callie
2 years ago
I believe option C is the correct answer. Using limited data can lead to inaccurate conclusions.
PA
Paris
2 years ago
I agree with Alysa. It's important to avoid overgeneralization and make sure our data is specific enough.
AL
Alysa
2 years ago
I think if you succumb to overgeneralization, you're using limited data to support broad conclusions.