X

Download The Teachers Beehive PowerPoint Presentation

SlidesFinder-Advertising-Design.jpg

Login   OR  Register
X


Iframe embed code :



Presentation url :

Home / Health & Wellness / Health & Wellness Presentations / The Teachers Beehive PowerPoint Presentation

The Teachers Beehive PowerPoint Presentation

Ppt Presentation Embed Code   Zoom Ppt Presentation

PowerPoint is the world's most popular presentation software which can let you create professional The Teachers Beehive powerpoint presentation easily and in no time. This helps you give your presentation on The Teachers Beehive in a conference, a school lecture, a business proposal, in a webinar and business and professional representations.

The uploader spent his/her valuable time to create this The Teachers Beehive powerpoint presentation slides, to share his/her useful content with the world. This ppt presentation uploaded by slidesfinder in Health & Wellness ppt presentation category is available for free download,and can be used according to your industries like finance, marketing, education, health and many more.

About This Presentation

Slide 1 - Normal Distributions and z-scores Hello 2014 – Further maths
Slide 2 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution
Slide 3 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean:
Slide 4 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side)
Slide 5 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side)
Slide 6 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side)
Slide 7 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean
Slide 8 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve
Slide 9 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1
Slide 10 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134
Slide 11 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4)
Slide 12 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5
Slide 13 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175
Slide 14 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm
Slide 15 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm The advantage of the summary chart is for a question like this (not symmetrical): What % of these women have heights between 165cm and 180cm? Answer: 34% + 34% + 13.5% = 81.5% 81.5% of women have heights between 165cm and 180cm
Slide 16 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm The advantage of the summary chart is for a question like this (not symmetrical): What % of these women have heights between 165cm and 180cm? Answer: 34% + 34% + 13.5% = 81.5% 81.5% of women have heights between 165cm and 180cm Z-scores We can also determine how many standard deviations above or below the mean a value lies by standardising the data. The standardised scores are called z-scores. To calculate z-score:
Slide 17 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm The advantage of the summary chart is for a question like this (not symmetrical): What % of these women have heights between 165cm and 180cm? Answer: 34% + 34% + 13.5% = 81.5% 81.5% of women have heights between 165cm and 180cm Z-scores We can also determine how many standard deviations above or below the mean a value lies by standardising the data. The standardised scores are called z-scores. To calculate z-score: Example 1 A set of data has a mean of 65 and a standard deviation of 6. Standardise the following scores: 53 68 75
Slide 18 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm The advantage of the summary chart is for a question like this (not symmetrical): What % of these women have heights between 165cm and 180cm? Answer: 34% + 34% + 13.5% = 81.5% 81.5% of women have heights between 165cm and 180cm Z-scores We can also determine how many standard deviations above or below the mean a value lies by standardising the data. The standardised scores are called z-scores. To calculate z-score: Example 1 A set of data has a mean of 65 and a standard deviation of 6. Standardise the following scores: 53 68 75 Example 1 – solution a) so a score value of 53 is two standard deviations below the mean b) So a value of 68 is 0.5 standard deviations above the mean c) So a value of 75 is 1.67 standard deviations above the mean
Slide 19 - Normal Distributions and z-scores Hello 2014 – Further maths The normal distribution Standard deviation is a measure of the spread of a data distribution about the average (mean) For normal distributions, we can determine the % of values that lie within 1, 2 or 3 standard deviations of the mean: 68% of values lie within 1 standard deviation of the mean (with 16% of values either side) 95% of values lie within 2 standard deviations of the mean (with 2.5% of values either side) 99.7% of values lie within 3 standard deviations of the mean (with 0.15% of values either side) 50% of values lie either side of the mean Summary diagram The diagram below can be used in all cases. It shows the % of values that lie in each section of the normal distribution curve Example 1 We always start by drawing diagrams. Each diagram below has been scaled with a mean of 134 and standard deviation of 20 134 154 114 94 174 134 134 194 74 Diagram 1 Diagram 3 Diagram 2 Diagram 4 134 Example 1 – solutions a) About 68% of executives have blood pressure between 114 and 154 (diagram 1) b) About 95% of executives have blood pressure between 94 and 174 (diagram 2) c) About 99.7% of executives have blood pressure between 74 and 194 (diagram 3) d) About 16% of executives have blood pressures above 154 (diagram 1) e) About 2.5% of executives have blood pressures below 94 (diagram 2) f) About 0.15% of executives have blood pressures below 74 (diagram 3) g) About 50% of executives have blood pressures above 134 (diagram 4) Example 2 For this question we could again use the four separate diagrams that were used in example 1, but instead we can use the summary diagram (see next page). Again a scale is included for a mean of 170 and standard deviation of 5 170 155 160 165 185 180 175 Example 2 – solutions a) Between 155cm and 185cm: 2.35% + 13.5% + 34% + 34% + 13.5% + 2.35% = 99.7% More than 175cm: 13.5% + 2.35% + 0.15% = 16% More than 170cm: 34% + 13.5% + 2.35% + 0.15% = 50% Less than 160cm: 2.35% + 0.15% = 2.5% Less than 165cm: 13.5% + 2.35% + 0.15% = 16% Between 160cm and 180cm: 13.5% + 34% + 34% + 13.5% = 95% We already found that 16% are likely to have heights above 170cm. 16% of 5000 = 0.16 x 5000 = 800 So 800 women are expected to have heights above 170cm The advantage of the summary chart is for a question like this (not symmetrical): What % of these women have heights between 165cm and 180cm? Answer: 34% + 34% + 13.5% = 81.5% 81.5% of women have heights between 165cm and 180cm Z-scores We can also determine how many standard deviations above or below the mean a value lies by standardising the data. The standardised scores are called z-scores. To calculate z-score: Example 1 A set of data has a mean of 65 and a standard deviation of 6. Standardise the following scores: 53 68 75 Example 1 – solution a) so a score value of 53 is two standard deviations below the mean b) So a value of 68 is 0.5 standard deviations above the mean c) So a value of 75 is 1.67 standard deviations above the mean Holiday homework Holiday homework must be completed neatly and accurately and submitted first lesson back in 2014. It is a work requirement and must be completed. You will be tested on chapters 1-3 in the first week back. Your holiday homework is all questions from the chapter reviews from chapters 1, 2 and 3