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miss Akunina [59]
3 years ago
5

Davi is mapping out essential and non-essential expenses and is perplexed about where to categorize gift-giving. Davi considers

splitting gifts into 4 different spending categories (Essential—Fixed, Essential—Variable, Non-Essential, and Other—Predictable). Then, he decides that 4 categories would be too complicated. He thinks that it will be simpler to budget all gifts under one category only and decides on the category “Other (Predictable)”. In addition, he will open a special savings account only for gift expenses, both for known people and occasions, and for general gifts that he may decide to give in the future. Which statement below is not a reasonable reason for Davi’s decision to establish a separate account for gift expenses. a. Budgeting categories are exact, and gifts can fit into only one of them. b. He will be able to give both planned and unplanned gifts that he has budgeted for. c. He will still be able to cover other important living expenses. d. Simplifying will help assure that he can follow his budget plans.
Mathematics
1 answer:
Vinvika [58]3 years ago
3 0

Answer:

Step-by-step explanation:

It’s A- Budgeting categories are exact, and gifts can fit into only one of them. muda suckaaa no explanation needed

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Answer:

99% confidence interval for the population proportion of employed individuals is [0.104 , 0.224].

Step-by-step explanation:

We are given that a simple random sample of size n=250 individuals who are currently employed is asked if they work at home at least once per week.

Of the 250 employed individuals​ surveyed, 41 responded that they did work at home at least once per week.

Firstly, the pivotal quantity for 99% confidence interval for the population proportion is given by;

                              P.Q. = \frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } }  ~ N(0,1)

where, \hat p = sample proportion of individuals who work at home at least once per week = \frac{41}{250} = 0.164

           n = sample of individuals surveyed = 250

<em>Here for constructing 99% confidence interval we have used One-sample z proportion statistics.</em>

So, 99% confidence interval for the population proportion, p is ;

P(-2.5758 < N(0,1) < 2.5758) = 0.99  {As the critical value of z at 0.5%

                                             level of significance are -2.5758 & 2.5758}  

P(-2.5758 < \frac{\hat p-p}{\sqrt{\frac{\hat p(1-\hat p)}{n} } } < 2.5758) = 0.99

P( -2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } } < {\hat p-p} < 2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } } ) = 0.99

P( \hat p-2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } } < p < \hat p+2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } } ) = 0.99

<em>99% confidence interval for p</em> = [\hat p-2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } } , \hat p+2.5758 \times {\sqrt{\frac{\hat p(1-\hat p)}{n} } }]

= [ 0.164-2.5758 \times {\sqrt{\frac{0.164(1-0.164)}{250} } } , 0.164+2.5758 \times {\sqrt{\frac{0.164(1-0.164)}{250} } } ]

 = [0.104 , 0.224]

Therefore, 99% confidence interval for the population proportion of employed individuals who work at home at least once per week is [0.104 , 0.224].

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