Heya, are you able to give advice on my work that is due at 9 am tomorrow morning?

What is your question? We will do our best to help.

Silina Hiko - AS 3.10 Inference

Iâ€™m unsure of how to complete the shape, shift, overlap, Informal Confidence Interval, and Bootstrapping Confidence Interval of my assessment. :(( and Iâ€™m stressed as itâ€™s due tomorrow.

Dear @Silhik1 I am sorry you are in such stress. Unfortunately, the access to the document you shared is denied. Please, refer to the following videos for more guidance:

shape - YouTube

Center - YouTube

spread - YouTube

Bootstrapping process - YouTube

bootstrap CI - YouTube

conclusion making the call - YouTube

If you post your report (better in the body of your post) we can provide some feedback.

this is the document

(Attachment Silina Hiko - AS 3.10 Inference .pdf is missing)

The document you were trying to attach is not there.

Kia ora

At level 3 you need to integrate your statistical comments with context to ensure that you meet the standard. If you send me your data set I will show you how to do this

all the best

Mrs H

Iâ€™m unsure of how to complete the following parts; shape, shift, overlap, Informal Confidence Interval, and Bootstrapping Confidence Interval of my assessment.

That is a good start, @Silhik1 !

**Graph:**

The labeling of your graph must be more specific. In your heading you need to specify that it is the age of male and female patients re-admitted within 12 months.

**Shape:**

You correctly mention that the shapes of data for both male and female patients are skewed to the right. But then you state that it is symmetrical, which contradicts your original statement.

The shapes of the distributions for your data look skewed to the right. *This observation is an Achieved level statement.* You then may want to continue exploring this statement by explaining what that means in context (M) and why it might be happening (E). With age it is often because it is limited by zero on the left (as you canâ€™t have a negative age).

**Central tendency:**

You can also look into the central tendency: compare the median ages of males and females re-admitted within a 12 month period and see if the middle 50% (IQR) of the distributions overlap and if the medians are inside or outside each otherâ€™s boxes. *This statement is an Achieved level statement.* Then you can justify what that means in context (M) and provide a possible explanation with references (E).

**Spread:**

Then you can look into the overall spread (the difference between minimum and maximum ages of male and female patients) and compare their IQR. That gives you an idea of the variability of the data. For example, you can make a statement that the middle 50% of ages of female patients re-admitted to hospital within a 12 month period is larger than the middle 50% of ages of male patients re-admitted to hospital within the same period (support your statement with numbers). *This observation is an A level statement*. That indicates that there is more variability in the ages of female patients re-admitted to hospital. *This statement puts your observation in the context which is an M level*. Then, you can provide possible justification for this observation, maybe some links to your research as to why that might happen. *That would be an E level of discussion.*

In your graph the IQR for the age of female patients is larger; however in your report you state that the IQR for male patients is larger, you may want to check that you used the correct numbers in your calculations.

**Making an inference back to the population:**

For Level 3 you are expected to compare medians (or means) and make a reference back to the population based on the bootstrapping confidence interval. You do not require the graph in slide 3 with the informal confidence interval, that was Level 2. Your conclusion based on the bootstrapping confidence interval must state:

Zero is/is not included into bootstrapping confidence interval, therefore I cannot/can make a call that back in the population the median age of female patients re-admitted within a 12 month period is greater/smaller than the median age of male patients re-admitted within a 12 month period.

**Sampling variability:**

Good statement.

can you please right examples for each part using my graph up to excellence please

Kia ora

Can you confirm what your numeric variable is, you state it is age but your graph label is â€śreadmittedâ€ť.

If that is your assessment, not a practice task, that would be a plagiarism, we canâ€™t write your assessment for you unfortunately.

The numeric variable is the amount of times diabetic get readmitted within 12-months of being readmitted.

Kia ora

further to the other comments I am concerned about you purpose statement.

please read the following and let me know if you need further clarification.

Purpose Statement / comparative Questions for 3.10

Must include

â€˘ The Numeric variable that is being examined (height in cm)

â€˘ The Categorical variable being compared (Gender (female or male)

â€˘ Population

â€˘ Statistic (DIFFERENCE in sample median heights between boys and girls)

For example:

What is the difference in the median Red Blood Cell counts (RCC) for male

Australian athletes and female Australian athletes for Australian athletes from the Institute of Sport in 2012.

In your question your variable median age but you say you are investigating the â€śamount of times diabetics get readmitted within 12 months of being readmitted