# data[].attributes.headline
Create a short summary relating to your topic.

# data[].attributes.subject
Create a short summary relating to your topic.

# data[].attributes.body
Bullet point form (easy to read)

Visuals (if possible)

Video (Youtube or your own)

# data[].attributes.body
The measure of the distribution of points

Shows how scattered points are

Left skews, right skews, concentrated mounds

Also called dispersion or distribution

Reveals variation and range of data

Used to get quartile ranges/interquartile ranges

𝜎2=∑𝑖=1𝑁(𝑋𝑖−𝜇)2𝑁
- To find standard deviation

# data[].attributes.headline
O: Obvious is stating a simple thing you can see from the graph 

# data[].attributes.subject
O: Obvious is stating a simple thing you can see from the graph 

# data[].attributes.headline
S:describing what we can observe in the graph using specific names and details

# data[].attributes.subject
S:describing what we can observe in the graph using specific names and details

# data[].attributes.body
After sorting the data into numeral order, find the data in the middle. If there are two medians find the mean of the two.

# data[].attributes.body
The median is usually the average data in the given information.

# data[].attributes.body
Describe range of values in the shape.

State where the median is located.

USE SPECIFIC VALUES/NUMBERS.

# data[].attributes.headline
E: Evidence go further into detail on what you can see and evaluating on the numbers and help build your mean  

# data[].attributes.subject
E: Evidence go further into detail on what you can see and evaluating on the numbers and help build your mean  

# data[].attributes.headline
M:analysing the conclusion based on the observations and evidences and giving reasons .Also talking about the outliers

# data[].attributes.subject
M:analysing the conclusion based on the observations and evidences and giving reasons .Also talking about the outliers

# data[].attributes.body
The problem question is a question that you are wondering about the variables of your data.

The problem question is something that you need to answer with your data and should be worthwhile investigating.

# data[].attributes.body
Sampling Variability: The extent to which the value of a statistic differs across a series of samples, showing the average variation/distribution of data. There is a degree of uncertainty involved in making inferences to the larger population.

# data[].attributes.body
How much the data is skewed to the left/right/up/down from the comparison.

# data[].attributes.body
It must start with I wonder if and include a catergoical variable, numerical variable, a population you are collecting data from, a direction of your comparison and the words "tends to".

# data[].attributes.body
Determine specifically what type of shape the data has formed - skewed, uniform, bimodal etc.

# data[].attributes.body
how to make a dot plot

including intro, frequency table explained, dot plot explained

# data[].attributes.attachment_link.title
How to Make a Dot Plot | Math with Mr. J

# data[].attributes.body
Sampling Variability is the information and stats from a sample and how different random samples change the information creating variation

# data[].attributes.attachment_link.title
Understanding Standard deviation and other measures of spread in statistics

# data[].attributes.body
e.g: I wonder if the height of boys tends to be taller than the height of girls from year 11 at Rangitoto College 2024.

# data[].attributes.body
it is possible that both medians are within each other's box, but the samples still seem to show a significant shift. However, this is not a case that you need to know about in year 11.

# data[].attributes.body
Needs gathered data that is relevant to the question

Can be graphed via NZGrapher

Also known as Box & Whisker plot

Shows the range, median, IQ, UQ, min, max of the data

Data can be numerical or categorical

Able to show clear outliers

Allows you to easily compare two sets of data

Visualise shape and spread of data to make analyses

Organise large amounts of data

Simplified histograms

# data[].attributes.headline
Iterative method that is used to present set of data and used in computer tomography. 

# data[].attributes.subject
Iterative method that is used to present set of data and used in computer tomography. 

# data[].attributes.body
When describing the shape its important to list the statistical description such as

symmetrical = from the median split in half both sides are the same

Asymmetrical = both sides are not even when split in half

Unimodal = a frequency distribution that has only one peak

Bimodal = have a camel hump or having two curves that have their own points with a dip in the middle

Uniform = when it is symmetrical the same kind of like a cube shape

Bell shaped/normal curve = a curve that has one peak point and is normal

Right/left skewed = the peak point leaning to the left or to the right with a tail at the end

# data[].attributes.body
The middle number found by ordering all data points and picking out the one in the middle (or if there are two middle numbers, taking the mean of those two numbers).

# data[].attributes.body
box plots explained

# data[].attributes.attachment_link.title
Box and Whisker Plots Explained | Understanding Box and Whisker Plots (Box Plots) | Math with Mr. J

# data[].attributes.headline
If you are interested, there is some extra information below. It is NOT RECOMMENDED that you use this method in your year 11 Assessments.

# data[].attributes.subject
If you are interested, there is some extra information below. It is NOT RECOMMENDED that you use this method in your year 11 Assessments.

# data[].attributes.body
Where the comparing graphs overlap one another.

Compare the LQ (lower quartile) to the UQ (upper quartile) of the graphs to see whether they cross over or not.

Overlapping of 50%

Find median of data

See if medians overlap

# data[].attributes.body
Key special features of graphs consist of:

patterns or characteristics in the data that deviate significantly from what is expected based on typical behavior.

Outliers, clusters and gaps are special features.

(in the image above there are examples of gaps, outliers and clusters.)

# data[].attributes.attachment_link.title
Analysing and commenting on graphical output using OSEM

# data[].attributes.body
A dot plot represents data by placing a dot for each data point, whereas a box plot is used to compare multiple groups of data which shows the median, IQ, max and min values of the data.

# data[].attributes.body
If the median is in the middle of the box the spread is even and has a symmetrical shape.

# data[].attributes.body
Group 1 has a wider box than Group 2.

The heights of Group 1 are more spread than Group 2 because of the bigger 50% box.

Evidence

In my sample, Group 1's heights and more varied than Group 2's heights. This could be due to...

If we take a similar sample size from another area I think the spread would be smaller/bigger.

# data[].attributes.headline
To make the call there must be a gap between the line or data. If it's too close to see on your line use your data. Looking at the graph below you can clearly see that there is a gap between intervals.

# data[].attributes.subject
To make the call there must be a gap between the line or data. If it's too close to see on your line use your data. Looking at the graph below you can clearly see that there is a gap between intervals.

# data[].attributes.attachment_link.description
NZGrapher is a web based graphing tool. NZ Grapher was designed for New Zealand Schools by a New Zealand Teacher.

# data[].attributes.body
The DBM (distance between median) and OVS (overall visual spread) provides us in making a decision. OVS/DBM x 100 answers the question "what proportion of the OVS is the DBM". If the sample size is 30 with a percentage over (33%) there tends to be a difference between A and B. If the sample size is 100 and the percentage is over 20% there will also be a difference between A and B. Finally, if the sample size is 1000 and the percentage is over 10% there will also be a difference between A and B.

# data[].attributes.attachment_link.title
Making inference based on median shift and overall visible spread for a sample of 30