Sample Size Formula (Part 1) From Formula 7.2, an estimate for margin of error for a 95 % confidence interval is m = 2 p ^ 1 − p ^ n where n is the required sample size and p ^ is the sample proportion. Since we do not know a value for p ^ , we use a conservative estimate of 0.50 for p ^ . Replace p ^ with 0.50 in the formula and simplify.
Sample Size Formula (Part 1) From Formula 7.2, an estimate for margin of error for a 95 % confidence interval is m = 2 p ^ 1 − p ^ n where n is the required sample size and p ^ is the sample proportion. Since we do not know a value for p ^ , we use a conservative estimate of 0.50 for p ^ . Replace p ^ with 0.50 in the formula and simplify.
Solution Summary: The author explains how to simplify the given formula by replacing stackrelp with 0.50.
Sample Size Formula (Part 1) From Formula 7.2, an estimate for margin of error for a
95
%
confidence interval is
m
=
2
p
^
1
−
p
^
n
where
n
is the required sample size and
p
^
is the sample proportion. Since we do not know a value for
p
^
, we use a conservative estimate of
0.50
for
p
^
. Replace
p
^
with
0.50
in the formula and simplify.
Definition Definition Number of subjects or observations included in a study. A large sample size typically provides more reliable results and better representation of the population. As sample size and width of confidence interval are inversely related, if the sample size is increased, the width of the confidence interval decreases.
A smallish urn contains 25 small plastic bunnies - 7 of which are pink and 18 of
which are white. 10 bunnies are drawn from the urn at random with replacement, and
X is the number of pink bunnies that are drawn.
(a) P(X = 5)=[Select]
(b) P(X<6) [Select]
Elementary StatisticsBase on the same given data uploaded in module 4, will you conclude that the number of bathroom of houses is a significant factor for house sellprice? I your answer is affirmative, you need to explain how the number of bathroom influences the house price, using a post hoc procedure. (Please treat number of bathrooms as a categorical variable in this analysis)Base on the same given data, conduct an analysis for the variable sellprice to see if sale price is influenced by living area. Summarize your finding including all regular steps (learned in this module) for your method. Also, will you conclude that larger house corresponding to higher price (justify)?Each question need to include a spss or sas output.
Instructions:
You have to use SAS or SPSS to perform appropriate procedure: ANOVA or Regression based on the project data (provided in the module 4) and research question in the project file. Attach the computer output of all key steps (number) quoted in…
Elementary StatsBase on the given data uploaded in module 4, change the variable sale price into two categories: abovethe mean price or not; and change the living area into two categories: above the median living area ornot ( your two group should have close number of houses in each group). Using the resulting variables,will you conclude that larger house corresponding to higher price?Note: Need computer output, Ho and Ha, P and decision. If p is small, you need to explain what type ofdependency (association) we have using an appropriate pair of percentages.
Please include how to use the data in SPSS and interpretation of data.
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