UCLA Stats 10 ACTUAL UPDATED Questions and CORRECT
Answers
1. why do we study stats? gain understanding of world; make con-
clusions from limited data
2. what is an entire population study? a census
3. why do we study samples? population is almost always too big to
study directly
4. statistical inference making conclusions about the popula-
tion from the sample
5. biased samples sample not representative of population
6. Simple random sampling list population, select a sampling frame
by which to randomly select people one
by one; every person should have an
equal selection chance and every single
possible sample had equal chance of oc-
curring
7. data table row observation unit
8. data table column variable
9. numerical data how much or how many
10. categorical data tells what kind or what type
11. Is age as years, numeric or categorical? numeric is using solid number to com-
pare differences; categorical if used in a
demographics sense as labeling
12. summary tables
, express the frequency of a variable in
terms of the sample total or variable; ap-
plies to categorical data points
13. two way table a table for summarizing 2 categorical
variables
14. anecdotal data customer testimonials; from stat stand-
point cannot perform analysis
15. observational study observing subject, try not to interfere,
collect as much info as possible; conclu-
sions become that is possible that certain
variable can be associated to a certain
outcome (associated not directly caused)
16. experiments assign treatments (cond); try to con-
trol as many aspects as possible (every-
one having exact same conditions beside
control and treatment) therefore can say
difference between subject outcomes is
attributable to the treatment
17. placebo
18. confounding variable
19. treatment
20. response
21. dot plot plots numeric data points; not preferable
for large n
Answers
1. why do we study stats? gain understanding of world; make con-
clusions from limited data
2. what is an entire population study? a census
3. why do we study samples? population is almost always too big to
study directly
4. statistical inference making conclusions about the popula-
tion from the sample
5. biased samples sample not representative of population
6. Simple random sampling list population, select a sampling frame
by which to randomly select people one
by one; every person should have an
equal selection chance and every single
possible sample had equal chance of oc-
curring
7. data table row observation unit
8. data table column variable
9. numerical data how much or how many
10. categorical data tells what kind or what type
11. Is age as years, numeric or categorical? numeric is using solid number to com-
pare differences; categorical if used in a
demographics sense as labeling
12. summary tables
, express the frequency of a variable in
terms of the sample total or variable; ap-
plies to categorical data points
13. two way table a table for summarizing 2 categorical
variables
14. anecdotal data customer testimonials; from stat stand-
point cannot perform analysis
15. observational study observing subject, try not to interfere,
collect as much info as possible; conclu-
sions become that is possible that certain
variable can be associated to a certain
outcome (associated not directly caused)
16. experiments assign treatments (cond); try to con-
trol as many aspects as possible (every-
one having exact same conditions beside
control and treatment) therefore can say
difference between subject outcomes is
attributable to the treatment
17. placebo
18. confounding variable
19. treatment
20. response
21. dot plot plots numeric data points; not preferable
for large n
