In a large class of introductory Statistics​ students, the professor has each person toss a coin 22 times and calculate the proportion of his or her tosses that were heads. Complete parts a through d below. ​a) Confirm that you can use a Normal model here.   The Independence Assumption ▼   is not is satisfied because the sample proportions ▼   are are not independent of each other since one sample proportion ▼   does not affect can affect another sample proportion. The​ Success/Failure Condition ▼   is not is satisfied because np=nothing and nq=nothing​, which are both ▼   greater than or equal to less than 10. ​(Type integers or decimals. Do not​ round.) ​b) Use the 68–95–99.7 Rule to describe the sampling distribution model.   About​ 68% of the students should have proportions between nothing and nothing​, about​ 95% between nothing and nothing​, and about​ 99.7% between nothing and nothing. ​(Type integers or decimals rounded to four decimal places as needed. Use ascending​ order.) ​c) They increase the number of tosses to 70 each. Draw and label the appropriate sampling distribution model. Check the appropriate conditions to justify your model.   The Independence Assumption ▼   is is not satisfied because the sample proportions ▼   are not are independent of each other since one sample proportion ▼   can affect does not affect another sample proportion. The​ Success/Failure Condition ▼   is not is satisfied because np=nothing and nq=nothing​, which are both ▼   less than greater than or equal to 10. ​(Type integers or decimals. Do not​ round.) Use the graph below to describe the sampling distribution model.

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In a large class of introductory Statistics​ students, the professor has each person toss a coin
22
times and calculate the proportion of his or her tosses that were heads. Complete parts a through d below.
​a) Confirm that you can use a Normal model here.
 
The Independence Assumption
 
is not
is
satisfied because the sample proportions
 
are
are not
independent of each other since one sample proportion
 
does not affect
can affect
another sample proportion. The​ Success/Failure Condition
 
is not
is
satisfied because
np=nothing
and
nq=nothing​,
which are both
 
greater than or equal to
less than
10.
​(Type integers or decimals. Do not​ round.)
​b) Use the
68–95–99.7
Rule to describe the sampling distribution model.
 
About​ 68% of the students should have proportions between
nothing
and
nothing​,
about​ 95% between
nothing
and
nothing​,
and about​ 99.7% between
nothing
and
nothing.
​(Type integers or decimals rounded to four decimal places as needed. Use ascending​ order.)
​c) They increase the number of tosses to
70
each. Draw and label the appropriate sampling distribution model. Check the appropriate conditions to justify your model.
 
The Independence Assumption
 
is
is not
satisfied because the sample proportions
 
are not
are
independent of each other since one sample proportion
 
can affect
does not affect
another sample proportion. The​ Success/Failure Condition
 
is not
is
satisfied because
np=nothing
and
nq=nothing​,
which are both
 
less than
greater than or equal to
10.
​(Type integers or decimals. Do not​ round.)
Use the graph below to describe the sampling distribution model.
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