IRP Research Question

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Can you help me understand this Statistics question?

Using the attached IRP Research Question and Data Set Template 2018, add the following information into the document.
Your research question for your IRP. ANOVA example: “Is there a statistically significant difference between these groups (identify the groups) based on this characteristic (identify the characteristic)? Simple Linear Regression (SLR) example: “Is this factor (identify the factor) a statistically significant predictor of a characteristic (identify the characteristic) based on this data sample? The statistical question that you hope to answer by analyzing the data set you picked.
ANOVA Example:
H0: μ1 = μ2 = … = μn HA: Not all means are equal (i.e. μ1 ≠ μ2 or μ2 ≠ μ3 … μ1 ≠ μn)
Simple Linear Regression Example:
H0: β1 = 0 HA: β1 ≠ 0
The name, source, and a link to your data set. Also, include the number of records and attributes in the data set. You do not have to use all of the attributes or records in your analysis. Submit a copy of your data set at this time as an Excel File so I can give you hints on what you may have to do with your data to make it useful in answering your research question. Submit your completed IRP Template file with information 1 & 2 above as a PDF file. Then, submit your Excel Data File as a separate submission to this assignment so I can review and provide comments.True or false SPSS Quesetions
I’m trying to study for my Statistics course and I need some help to understand this question.

When you save either a Data View screen or a Variable View screen, both screens are saved together whether you click Save or Save As on the Main Menu. To save a database you have the choices Save and Save As. When using the Save As option to save data you are able to specify a new name but not a new location. When choosing the Save option, the two screens (Variable View and Data View) are saved to the active location and with its current name. Clicking on File on the Main Menu and then clicking on Save As opens a window titled Save Data As. To specify a location for a given dataset to be saved you need to click on the button next to the Look in box, which will give you a drop-down menu of the location/s. If you wish to change the file name or if you are saving new data that require a name, you would type the desired name in the File name box. The IBM SPSS Statistics software automatically assigns an extension of “.sav” to Output files. To open the dialog window titled Save Output As you need to click on File in Variable View screen and then click Save As. When you click Edit on the Main Menu, select Open, and then click Data a window titled Open Data will appear requesting that you locate the file you wish to open. Basically, science can be considered as the measurement and analysis of observations made by humans. The investigator does have some freedom when specifying levels of measurement for their research variables. Level of measurement is defined as a phrase that describes how measurable information was obtained while observing variables. The Measure column is located in the Data View screen. The IBM SPSS Statistics software program can consistently recognize the correct level of measurement that should be used to measure variables. We can only count and calculate the percentage of the total number of observations that occupy the various categories of a variable measured at the ordinal level. When using the IBM SPSS Statistics software the person trying to make sense of the data does not have to understand whether the variables were measured at the nominal, ordinal, or scale levels. The IBM SPSS Statistics software recognizes three levels of measurement that should be considered as a hierarchy: nominal (lowest level), then ordinal (middle level), and finally scale (highest level). When using the ordinal level of measurement, we say that the differences (distances) between ranks are equal and fixed. It is possible to calculate the median of the variable music which has an intensity ranking as follows: very low, low, medium, high, and very high.Give an example of an interval estimate of an average or proportion you may use in your daily life.: online nursing assignment help
Need help with my Statistics question – I’m studying for my class.

(200-250 words for initial post)

Give an example of an interval estimate of an average or proportion you may use in your daily life. For instance, you may say that you are pretty sure your average commute time is between 25-30 minutes, or you are fairly confident that between 60-65% of the population love dogs. Collect some data to see how well your intuition is working. First, does your sample data meet all assumptions necessary to construct the confidence interval of the type you need? Even if it doesn’t, construct and interpret the confidence interval.

(100 words each response to 2 class mates) Here below are 2 classmates discussions, they need 100 words each responses. The response should include the answer to the below question. (I will also attach their discussion questions on word documents so that it’s easier to read)

Collect your own data and find your own confidence interval and compare. If, for example, your point estimate is less than your classmate’s point estimate, can you be sure or confident that the corresponding parameter is less? Why or why not, and what could you do to try to figure it out? What impact do the bounds of the intervals have?

Classmate discussion #1

The estimate I am going to use is the amount of money I carry every day in my wallet. The data represents the amount of money in my wallet for a period of 25 days.

Amount ($)

112

156

192

57

45

153

106

152

49

77

189

250

50

175

129

72

84

185

95

202

206

150

142

145

192

The mean amount of money in my wallet is $134.6.

The standard deviation of money in my wallet is $57.53.

First, does your sample data meet all assumptions necessary to construct the confidence interval of the type you need? Yes, my sample data meet all assumptions necessary to construct the confidence interval:

1. The sample size of the data is 25.

2. The sample mean and sample standard deviation is defined.

3. In order to construct a confidence interval, I will choose a 95% Confidence interval.

Even if it doesn’t, construct and interpret the confidence interval.

95% Confidence Interval will be:

Z-score corresponding to 95% Confidence interval is 1.96.

Confidence Interval = Sample mean ± z*( Sample standard deviation/ Sample size)

= x̄ ± z*(σ/√n)

= 134.6 ± 1.96 * (57.53/√25)

= 134.6 ± 1.96 * 11.51

= 134.6 ± 22.5525

= ( 134.6 – 22.5525, 134.6 + 22.5525)

= ( 112.0475, 157.1525)

Therefore, 95% confidence interval for the amount of money in my wallet is between $112.0475 and $157.1525.

Classmate discussion #2

I wanted to check my average footsteps or how much I am walking daily. On an average I am walking around 50000 steps per week. This helps me in my health and fitness and it also reduces the time I have exercise daily. Based on the following data let us track the confidence interval for my footsteps. So on an average my daily level of walking is around 50000 / 7 = 7100 steps. Let us check this data with 95 percent confidence interval.

Confidence interval for proportion p is given by,

ME = 1.96 ^ (.142(.858) / 50000) = .0031

.142 – .0031 < p < .142 + .0031 .1389 < p < .1451 The above calculation shows my confidence interval as .1389 < p < .1451. As you can I determined this data using my step tracker. In that step tracker we can track our daily steps, monthly steps, yearly steps on an average. But the weekly average is not the same here and it may vary based on my daily level of walking. So s data does not satisfy the conditions of the Central Limit Theorem for proportions. Luckily, randomization tests for experiments do not have any assumptions, so we conduct the test using a randomization test. While obtaining the results for this test, it fairly showed the same output, which ultimately means that the data which we used may not be accurate but is fairly approximate. Since a difference of zero (no change) is not within this interval, it is plausible that there has been no big change in the pattern of my weekly steps. But this is not the same for daily steps. We are 95% confident that on an average my daily level of walking around 7000 steps will be between 0.1389 and .1451 points. Extra Resources! Go to your Textbook and read the following sections: Confidence Intervals · A Single Population Mean using the Normal Distribution · A Single Population Mean using the Student t Distribution · A Population Proportion Additionally, watch the following videos: · https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/conditions-for-valid-confidence-intervals · https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/conditions-for-confidence-intervals-worked-examples · https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/critical-value-for-a-given-confidence-level · https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/example-calculating-confidence-interval · https://www.khanacademy.org/math/ap-statistics/estimating-confidence-ap/one-sample-z-interval-proportion/v/determining-sample-size-based-on-confidence-and-margin-of-error

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