Mathematics Assessment: Please read carefully!!!!

Read all steps before opening and using the data sheet.  Do not waste any of the double period we have as this will impact how much of the assessment we get through.


Statistics Multivariate data.

Using the information you gathered from the Maketu Estuary you will compare they samples of the species evident during your observation.

I have attached the spreadsheet of data.
On the first sheet it has the data collected at each transect and the distance along the transect which it was collected.  This is useful information for discussing why certain species were more evident at different parts of the estuary.

For the data to be displayed in a box and whisker we need to sort into species.  I have set up a table for you to put the data into.  You will need to organise yourselves into 4 groups.  This way you only need to sort around 30 samples each rather than the entire data set.  Each group will sort 3 transect lines worth of data for each of the four species.  E.g Group 1 will put the information for transect 1, 2 & 3 and place the numbers collected under the headings for Amphibola crenata, Zeacumantus lutulentus, Gracilaria (% cover) & Ulva lactuca (% cover).

Once you have completed this you can make a copy of one of the tables and use this for your assessment.
You must sort the data from smallest to biggest for each species (Amphibola crenata, Zeacumantus lutulentus, Gracilaria (% cover) & Ulva lactuca (% cover)). Then work out the summary statistics, Minimum, lower quartile, median, upper quartile, maximum, range & interquartile range.

You are required to complete a full PPDAC cycle so need to make a question, prediction and plan can be written using the science experiements (you may want to wait until I am back before completing this part and focus on sorting the data and drawing the graphs first.

You can then place this information into a box and whisker for each species (so four boxes in total), and place the dots above the boxes to show spread.
Then make the necessary comments for the analysis section and conclusion.

Here is the link to access the spreadsheet.
Spreadsheet of data

Visual Text

Statistics Practice paper

I will attach this practice task to the google classroom for you to complete this Monday.This is here in case you have any issues using the attachment, copy and paste this information into another document.

Student instructions sheet

Introduction

This activity requires you to undertake a statistical investigation using a randomly selected sample from a list of countries of the world. First, you will pose two investigative questions. Then you will analyse the sample and form a conclusion for one of your questions.

This activity is to be completed independently.

You will be assessed on the quality of your discussion and reasoning and how well you link this to the context.

Task

Carry out a statistical investigation on the The World at a Glance sample using the statistical enquiry cycle (Problem, Plan, Data, Analysis, Conclusion).

Problem

Pose two investigative questions about countries that can be explored using The World at a Glance dataset. See Student Resource A for a description of the variables.

Your investigative questions must be comparison questions. A suitable comparison investigative question is one that reflects the population, has a clear variable to investigate, compares the values of a continuous variable across different categories, and can be answered with the data.

For each question, state the variable you are investigating and the groups you are comparing.

Now choose one of your two questions for investigation using the data found in Student Resource B.

Plan and data

Because the 60 countries in Student Resource B were selected using a random sampling technique, the sample can be considered representative of all the countries in the database.

Analysis

Draw at least two appropriate graphs that show different features of the data in relation to your investigative question.

Give appropriate summary statistics.

Describe features of the distributions comparatively (for example, shape, middle 50%, shift, overlap, spread, unusual or interesting features).

Conclusion

Write a conclusion summarising your findings. The conclusion needs to include an informal inference in response to your investigative question and to be supported with relevant evidence.

Student Resource A: The World at a Glance variables

The table below shows the values for the six variables included in the dataset in Student Resource B.

The variables in the dataset and explanations of how the variables were collected are:

Variable	Explanation
Country	Randomly selected countries
Climate	Tropical countries are hot and around the equator, temperate countries are colder and lie between the tropics and the poles (tropical, temperate)
Level of development	High means developed countries and low means developing countries
TV Sets	The number of households that have television (per 1000 people)
Literacy rate (%)	The percent of the population in that country that can read
Internet use (%)	The percent of the population in that country that use the internet

This data has been collated using the most recently available information, and can be assumed to describe countries during the year 2013.

Student Resource B: The World at a Glance dataset

See Student Resource A for a list of variables.

	* = data unavailable
	Country	Climate	Level of Development	TV sets	Literacy rate (%)	Internet Use (%)
1	Argentina	Tropical	High	223	98	56
2	Austria	Temperate	High	533	98	81
3	Bangladesh	Tropical	Low	6	58	6
4	Bolivia	Tropical	Low	115	91	43
5	Brazil	Tropical	High	219	90	50
6	Canada	Temperate	High	717	99	87
7	Chile	Temperate	High	212	99	61
8	China	Temperate	Low	325	95	42
9	Colombia	Tropical	High	116	94	49
10	Denmark	Temperate	High	590	99	93
11	Ecuador	Tropical	High	132	93	35
12	Egypt	Tropical	Low	121	74	44
13	Ethiopia	Tropical	Low	503	39	2
14	France	Temperate	High	598	99	83
15	Georgia	Temperate	High	526	100	46
16	Germany	Temperate	High	567	99	84
17	Ghana	Tropical	Low	93	72	17
18	Hong Kong	Tropical	High	284	94	73
19	India	Tropical	Low	65	74	13
20	Indonesia	Tropical	Low	69	90	15
21	Iran	Tropical	High	76	85	26
22	Iraq	Tropical	Low	76	78	7
23	Italy	Temperate	High	533	99	58
24	Jamaica	Tropical	High	182	88	47
25	Japan	Temperate	High	686	99	79
26	Kenya	Tropical	Low	25	87	32
27	Korea, North	Tropical	Low	56	99	*
28	Korea, South	Tropical	High	346	98	84
29	Kyrgyzstan	Temperate	Low	44	99	22
30	Lithuania	Temperate	High	475	100	68
31	Mali	Tropical	Low	4	28	2
32	Mexico	Tropical	High	273	93	38
33	Mauritania	Tropical	Low	26	58	5
34	Morocco	Tropical	Low	114	67	55
35	Myanmar (Burma)	Tropical	Low	592	93	1
36	Netherlands	Temperate	High	519	99	93
37	New Zealand	Temperate	High	509	99	90
38	Pakistan	Temperate	Low	24	57	10
39	Panama	Tropical	High	183	92	45
40	Peru	Tropical	High	124	93	38
41	Philippines	Tropical	Low	52	93	36
42	Poland	Temperate	High	338	100	65
43	Portugal	Temperate	High	328	95	64
44	Romania	Temperate	High	6	98	50
45	Russia	Temperate	High	411	100	53
46	Samoa	Tropical	Low	64	100	13
47	Singapore	Tropical	High	351	93	74
48	South Africa	Temperate	Low	127	93	41
49	Spain	Temperate	High	409	98	72
50	Sudan	Tropical	Low	77	71	21
51	Taiwan	Tropical	High	3	98	76
52	Tanzania	Tropical	Low	3	69	13
53	Thailand	Tropical	Low	255	93	27
54	Turkey	Temperate	High	326	95	45
55	Ukraine	Temperate	High	3	100	34
56	United Kingdom	Temperate	High	522	99	87
57	United States	Temperate	High	803	99	81
58	Venezuela	Tropical	High	179	93	44
59	Vietnam	Tropical	Low	47	94	40
60	Zambia	Tropical	Low	24	81	14