1. © 2011 REACH All Rights Reserved.Fall 2011

2. Mathematical Functions Statistical Functions Information Functions Lookup Functions Date Functions Time Functions Text Functions Database Functions

3. SUMIF =SUMIF(range,criteria,[sum_range])

4. Microsoft ® Excel ® Mathematical Functions Syntax: =SUMIF(range, criteria, [sum_range]) Arguments: range Required  The range of cells that you want evaluated by criteria. o Cells in each range must be numbers or names, arrays, or references that contain numbers. o Blank and text values are ignored.  criteria Required  The criteria in the form of a number, expression, a cell reference, text, or a function that defines which cells will be added. o Criteria can be expressed as 32, ">32", B5, "32", "apples", or TODAY(). sum_range Optional  The actual cells to add, if you want to add cells other than those specified in the range argument. o Excel adds the cells that are specified in the range argument (the same cells to which the criteria is applied).

5. Microsoft ® Excel ® Mathematical Functions Description: Sums the values in a range that meet criteria that you specify. Remarks: See the Microsoft ® Excel ® help for additional remarks. Errors: None

6. Microsoft ® Excel ® Mathematical Functions

7. AVERAGEIF =AVERAGEIF(range,criteria,[average_range]) COUNTIF =COUNTIF(range, criteria)

8. Microsoft ® Excel ® Statistical Functions Syntax: =AVERAGEIF(range, criteria, [average_range]) Arguments: range Required  One or more cells to average, including numbers or names, arrays, or references that contain numbers. criteria Required  The criteria in the form of a number, expression, cell reference, or text that defines which cells are averaged. average_range Optional  The actual set of cells to average.

9. Microsoft ® Excel ® Statistical Functions Description: Returns the average (arithmetic mean) of all the cells in a range that meet a given criteria. Remarks: If average_range is omitted, range is used. Cells in range that contain TRUE or FALSE are ignored. If a cell in average_range is an empty cell, AVERAGEIF ignores it. If a cell in criteria is empty, AVERAGEIF treats it as a 0 value. Errors: #DIV/0 – If range is a blank or text value. #DIV/0 – If no cells in the range meet the criteria.

10. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(B2:B5,"<23000")

11. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(B2:B5,"<23000") =14000

12. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(A2:A5,"<95000")

13. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(A2:A5,"<95000") =#DIV/0

14. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(A2:A5,">250000",B2:B5)

15. Microsoft ® Excel ® Statistical Functions =AVERAGEIF(A2:A5,">250000",B2:B5) =24500

16. Microsoft ® Excel ® Statistical Functions Syntax: =COUNTIF(range, criteria) Arguments: range Required  One or more cells to count, including numbers or names, arrays, or references that contain numbers. o Blank and text values are ignored.  criteria Required  A number, expression, cell reference, or text string that defines which cells will be counted. o Criteria can be expressed as 32, ">32", B4, "apples", or "32".

17. Microsoft ® Excel ® Statistical Functions Description: Counts the number of cells within a range that meet a single criterion that you specify. Remarks: See the Microsoft ® Excel ® help for additional remarks. Criteria are case insensitive Errors: None

18. Microsoft ® Excel ® Statistical Functions

19. ISERR =ISERR(value) ISERROR =ISERROR(value) ISNA =ISNA(value)

20. Microsoft ® Excel ® Information Functions Syntax: =ISERR(value) Arguments: value Required  The value that you want tested

21. Microsoft ® Excel ® Information Functions Description: Returns TRUE if value refers to any error value except #N/A. Remarks: The value arguments of the IS functions are not converted Any numeric values that are enclosed in double quotation marks are treated as text. The IS functions are useful in formulas for testing the outcome of a calculation Errors: None

22. Microsoft ® Excel ® Information Functions Syntax: =ISERROR(value) Arguments: value Required  The value that you want tested

23. Microsoft ® Excel ® Information Functions Description: Returns TRUE if value refers to any error value: #N/A#VALUE!#REF!#DIV/0! #NUM!#NAME?#NULL! Remarks: The value arguments of the IS functions are not converted Any numeric values that are enclosed in double quotation marks are treated as text. The IS functions are useful in formulas for testing the outcome of a calculation Errors: None

24. Microsoft ® Excel ® Information Functions Syntax: =ISNA(value) Arguments: value Required  The value that you want tested

25. Microsoft ® Excel ® Information Functions Description: Returns TRUE if value refers to the #N/A (value not available) error value. Remarks: The value arguments of the IS functions are not converted Any numeric values that are enclosed in double quotation marks are treated as text. The IS functions are useful in formulas for testing the outcome of a calculation Errors: None

26. Microsoft ® Excel ® Information Functions

28. VLOOKUP =VLOOKUP(lookup_value, table_array, col_index_num, [range_lookup])

29. Microsoft ® Excel ® Lookup Functions Syntax: =VLOOKUP(lookup_value,table_array,col_index_num,[range_lookup]) Arguments: lookup_value Required  The value to search in the first column of the table or range. table_array Required  The range of cells that contains the data. col_index_num Required  The column number in the table_array argument from which the matching value must be returned. range_lookup Optional  A logical value that specifies whether you want VLOOKUP to find an exact match or an approximate match.

30. Microsoft ® Excel ® Lookup Functions Description: Searches the first column of a range of cells, and then returns a value from any cell on the same row of the range. Remarks: The values in the first column of table_array can be text, numbers, or logical values. Uppercase and lowercase text are equivalent. If range_lookup is TRUE, the values in the first column of table_array must be placed in ascending order. If range_lookup is TRUE or omitted, an approximate match is returned. If range_lookup is FALSE, an exact match will be attempted.

31. Microsoft ® Excel ® Lookup Functions Errors: #VALUE! – If col_index_num is less than 1 #REF! – If col_index_num is greater than the number of columns in the table_array #N/A – If range_lookup is FALSE and an exact match cannot be found #N/A – If lookup_value is less than the smallest value in the first column of table_array

32.  Use IS functions with VLOOKUP functions to avoid seeing errors when your lookup values are not found or when the result are empty cells.  Example: =IF(ISNA(VLOOKUP(C2,Customers,2,FALSE)),"",( VLOOKUP(C2,Customers,2,FALSE))) The function above will only return the result of the VLOOKUP when VLOOKUP does not give a #N/A error. If the VLOOKUP function does return a #N/A error, the If statement will return nothing.

33. Microsoft ® Excel ® Lookup Functions Syntax: =INDEX(array,row_num,[column_num]) Arguments: array Required  A range of cells or an array constant. row_num Optional  Selects the row in array from which to return a value. o If row_num is omitted, column_num is required. column_num Optional  Selects the column in array from which to return a value. o If column_num is omitted, row_num is required.

34. Microsoft ® Excel ® Lookup Functions Description: Returns the value of an element in a table or an array, selected by the row and column number indexes. Remarks: If both the row_num and column_num arguments are used, INDEX returns the value in the cell at the intersection of row_num and column_num. Errors: #REF! – If row_num and column_num do not point to a cell within array

35. Microsoft ® Excel ® Lookup Functions

36. Syntax: =MATCH(lookup_value, lookup_array, [match_type]) Arguments: lookup_value Required  The value that you want to match in lookup_array. lookup_array Required  The range of cells being searched. match_type Optional  Specifies how Excel matches lookup_value with values in lookup_array. o The number -1, 0, or 1

37. Microsoft ® Excel ® Lookup Functions Description: Searches for a specified item in a range of cells, and then returns the relative position of that item in the range Remarks: The lookup_value argument can be a value (number, text, or logical value) or a cell reference to a number, text, or logical value. MATCH returns the position of the matched value within lookup_array, not the value itself. MATCH does not distinguish between uppercase and lowercase letters when matching text values. Errors: #N/A – If MATCH is unsuccessful in finding a match

38. Microsoft ® Excel ® Lookup Functions ValueBehaviorRestrictions 1 MATCH finds the largest value that is less than or equal to lookup_value. The values in the lookup_array argument must be placed in ascending order. 0 MATCH finds the first value that is exactly equal to lookup_value. None MATCH finds the smallest value that is greater than or equal to lookup_value. The values in the lookup_array argument must be placed in descending order. Default

39. Microsoft ® Excel ® Lookup Functions

40. TODAY =TODAY() NOW =NOW() YEARFRAC =YEARFRAC(start_date,end_date,[basis]) DATEDIF =DATEDIF(startdate,enddate,interval)

41. Microsoft ® Excel ® Date Functions Syntax: =DATE(year,month,day) Arguments: year Required  The value of the year argument can include one to four digits. month Required  A positive or negative integer representing the month of the year from 1 to 12 (January to December). day Required  A positive or negative integer representing the day of the month from 1 to 31.

42. Microsoft ® Excel ® Date Functions Description: Returns the sequential serial number that represents a particular date. Remarks: If the cell format was General before the function was entered, the result is formatted as a date instead of a number. Excel interprets the year argument according to the date system your computer is using. By default, Microsoft Excel for Windows uses the 1900 date system; Microsoft Excel for the Macintosh uses the 1904 date system. Excel stores dates as sequential serial numbers so that they can be used in calculations. Errors: None

43. Microsoft ® Excel ® Date Functions =DATE(A2,B2,C2) What is the serial date for the date in A2:C2, using the 1900 date system?

44. Microsoft ® Excel ® Date Functions =DATE(A2,B2,C2) =39448 What is the serial date for the date in A2:C2, using the 1900 date system?

45. Microsoft ® Excel ® Date Functions Syntax: =TODAY() Arguments: None

46. Microsoft ® Excel ® Date Functions Description: Returns the serial number of the current date. Remarks: If the cell format was General before the function was entered, Excel changes the cell format to Date. If you want to view the serial number, you must change the cell format to General or Number. The TODAY function is useful when you need to have the current date displayed on a worksheet, regardless of when you open the workbook. The TODAY function is dependent on your computer’s system clock being correct. Errors: None

47. Microsoft ® Excel ® Date Functions =TODAY()

48. Microsoft ® Excel ® Date Functions =TODAY()

49. Microsoft ® Excel ® Date Functions Syntax: =NOW() Arguments: None

50. Microsoft ® Excel ® Date Functions Description: Returns the serial number of the current date and time. Remarks: If the cell format was General before the function was entered, Excel changes the cell format to the same date and time format that is specified in the regional date and time settings in Control Panel. The NOW function is useful when you need to display the current date and time on a worksheet or calculate a value based on the current date and time, and have that value updated each time you open the worksheet. Numbers to the right of the decimal point in the serial number represent the time; numbers to the left represent the date. The results of the NOW function change only when the worksheet is calculated or when a macro that contains the function is run. It is not updated continuously. Errors: None

51. Microsoft ® Excel ® Date Functions =NOW()

52. Microsoft ® Excel ® Date Functions =NOW()

53. Microsoft ® Excel ® Date Functions Syntax: =YEARFRAC(start_date,end_date,[basis]) Arguments: start_date Required  A date that represents the start date. end_date Required  A date that represents the end date. basis Optional  The type of day count basis to use.

54. Microsoft ® Excel ® Date Functions Description: Calculates the fraction of the year represented by the number of whole days between two dates (the start_date and the end_date). Remarks: Use the YEARFRAC worksheet function to identify the proportion of a whole year's benefits or obligations to assign to a specific term. Dates should be entered by using the DATE function, or as results of other formulas or functions. All arguments are truncated to integers. Errors: #VALUE – If start_date or end_date are not valid dates #NUM! – If basis < 0 #NUM! – If basis > 4

55. Microsoft ® Excel ® Date Functions =YEARFRAC(A2,A3,A4) What is the fraction of the year between the two dates?

56. Microsoft ® Excel ® Date Functions =YEARFRAC(A2,A3,A4) =0.583333333 What is the fraction of the year between the two dates?

57. Microsoft ® Excel ® Date Functions Syntax: =DATEDIF(startdate,enddate,interval) Arguments: startdate Required  A date that represents the start date. enddate Required  A date that represents the end date. interval Required  The type of day count basis to use.

58. Microsoft ® Excel ® Date Functions Syntax: =DATEDIF(startdate,enddate,interval) Arguments: interval Required  The type of day count basis to use.

59. Microsoft ® Excel ® Date Functions Description: Computes the difference between two dates in a variety of different intervals. Remarks: If you have the interval in another cell referenced by the formula, that cell should not have quotes around the interval string. When calculating date intervals, DATEDIF uses the year of startdate, not enddate when calculating the yd, ym and md intervals Errors: #VALUE – If start_date or end_date are not valid dates #NUM! – If start date is not less than or equal to the end date

60. Microsoft ® Excel ® Date Functions =DATEDIF(A2,A3,”d”) What is the difference in days between the two dates?

61. Microsoft ® Excel ® Date Functions =DATEDIF(A2,A3,”d”) =210 What is the difference in days between the two dates?

62. FIND =FIND(find_text,within_text,[start_num]) LEFT =LEFT(text,[num_chars]) LEN =LEN(text) RIGHT =RIGHT(text,[num_chars]) CONCATENATECONCATENATE (including &) =CONCATENATE(text1, [text2],...) UPPER =UPPER(text) LOWER =LOWER(text) PROPER =PROPER(text)

63. Microsoft ® Excel ® Text Functions Syntax: =FIND(find_text,within_text,[start_num]) Arguments: find_text Required  The text you want to find. within_text Required  The text string containing the text you want to find. start_num Optional  Specifies the character at which to start the search.

64. Microsoft ® Excel ® Text Functions Description: Locates one text string within a second text string, and returns the number of the starting position of the first text string from the first character of the second text string Remarks: FIND always counts each character. The first character in within_text is character number 1. If you omit start_num, it is assumed to be 1. FIND is case sensitive. If find_text is "" (empty text), FIND matches the first character in the search string (that is, the character numbered start_num or 1).

65. Microsoft ® Excel ® Text Functions Errors: #VALUE! – If find_text does not appear in within_text #VALUE! – If start_num is not greater than zero #VALUE! – If start_num is greater than the length of within_text

66. Microsoft ® Excel ® Text Functions A 11Miriam McGovern =FIND(“M”,A11) =1

67. Microsoft ® Excel ® Text Functions A 11Miriam McGovern =FIND(“M”,A11,3) =8

68. Microsoft ® Excel ® Text Functions A 11Miriam McGovern =FIND(“m”,A11) =6

69. Microsoft ® Excel ® Text Functions Syntax: =LEFT(text,[num_chars]) Arguments: text Required  The text string that contains the characters you want to extract. num_chars Optional  Specifies the number of characters you want LEFT to extract.

70. Microsoft ® Excel ® Text Functions Description: Returns the first character or characters in a text string, based on the number of characters you specify Remarks: LEFT always counts each character. Num_chars must be => 0.

71. Microsoft ® Excel ® Text Functions A 1Data 2Sale Price =LEFT(A2,4) =Sale

72. Microsoft ® Excel ® Text Functions A 1Data 2Sale Price 3Sweden =LEFT(A3) =S

73. Microsoft ® Excel ® Text Functions Syntax: =LEN(text) Arguments: text Required  The text whose length you want to find.

74. Microsoft ® Excel ® Text Functions Description: Returns the number of characters in a text string. Remarks: Spaces count as characters.

75. Microsoft ® Excel ® Text Functions A 1Data 2Phoenix, AZ 3 4 5 6 One =LEN(A2) =11

76. Microsoft ® Excel ® Text Functions A 1Data 2Phoenix, AZ 3 4 5 6 One =LEN(A4) =0

77. Microsoft ® Excel ® Text Functions A 1Data 2Phoenix, AZ 3 4 5 6 One =LEN(A6) =8

78. Microsoft ® Excel ® Text Functions Syntax: =RIGHT(text,[num_chars]) Arguments: text Required  The text string that contains the characters you want to extract. num_chars Optional  Specifies the number of characters you want RIGHT to extract.

79. Microsoft ® Excel ® Text Functions Description: Returns the last character or characters in a text string, based on the number of characters you specify. Remarks: RIGHT always counts each character. Num_chars must be => 0.

80. Microsoft ® Excel ® Text Functions A 1Data 2Sale Price 3 4Stock Number =RIGHT(A2,5) =Price

81. Microsoft ® Excel ® Text Functions A 1Data 2Sale Price 3 4Stock Number =RIGHT(A2,LEN(A2)-FIND(“ “,A2)) =RIGHT(A2,10-5) =RIGHT(A2,5) =Price

82. Microsoft ® Excel ® Text Functions A 1Data 2Sale Price 3 4Stock Number =RIGHT(A4) =r

83. Microsoft ® Excel ® Text Functions Syntax: =CONCATENATE(text1, [text2],...) Arguments: text1 Required  The first text item to be concatenated. text2 Optional  Additional text items, up to a maximum of 255 items, which must be separated by commas.

84. Microsoft ® Excel ® Text Functions Description: Joins up to 255 text strings into one text string. Remarks: The joined items can be text, numbers, cell references, or a combination of those items.

85. Microsoft ® Excel ® Text Functions ABC 1Data 2Brook troutAndreasHauser 3speciesFourthPine 432 =CONCATENATE(“Stream Population for “,A2,” “,A3, “ is “,A4,”/mile”) =Stream Population for Brook trout species is 32/mile

86. Microsoft ® Excel ® Text Functions ABC 1Data 2Brook troutAndreasHauser 3speciesFourthPine 432 =CONCATENATE(B2, “ “, C2) =Andreas Hauser

87. Microsoft ® Excel ® Text Functions ABC 1Data 2Brook troutAndreasHauser 3speciesFourthPine 432 =CONCATENATE(C2, “, “, B2) =Hauser, Andreas

88. Microsoft ® Excel ® Text Functions ABC 1Data 2Brook troutAndreasHauser 3speciesFourthPine 432 =CONCATENATE(B3, “ & “, C3) =Fourth & Pine

89. Microsoft ® Excel ® Text Functions ABC 1Data 2Brook troutAndreasHauser 3speciesFourthPine 432 =B3& “ & “ &C3 =Fourth & Pine

90. Microsoft ® Excel ® Text Functions Syntax: =UPPER(text) Arguments: text Required  The text you want converted to uppercase.

91. Microsoft ® Excel ® Text Functions Description: Converts text to uppercase. Remarks: Text can be a reference or text string.

92. Microsoft ® Excel ® Text Functions =UPPER(A2) =TOTAL

93. Microsoft ® Excel ® Text Functions =UPPER(A3) =YIELD

94. Microsoft ® Excel ® Text Functions Syntax: =LOWER(text) Arguments: text Required  The text you want converted to lowercase.

95. Microsoft ® Excel ® Text Functions Description: Converts all uppercase letters in a text string to lowercase. Remarks: LOWER does not change characters in text that are not letters.

96. Microsoft ® Excel ® Text Functions =LOWER(A2) =e.e. cummings

97. Microsoft ® Excel ® Text Functions =LOWER(A3) =apt. 2b

98. Microsoft ® Excel ® Text Functions Syntax: =PROPER(text) Arguments: text Required  Text enclosed in quotation marks, a formula that returns text, or a reference to a cell containing the text you want to partially capitalize.

99. Microsoft ® Excel ® Text Functions Description: Capitalizes the first letter in a text string and any other letters in text that follow any character other than a letter. Remarks: PROPER converts all other letters to lowercase letters.

100. Microsoft ® Excel ® Text Functions =PROPER(A2) =This Is A Title

101. Microsoft ® Excel ® Text Functions =PROPER(A3) =2-Cent’S Worth

102. Microsoft ® Excel ® Text Functions =PROPER(A4) =76Budget

103.  The TRIM function removes leading and trailing spaces from the input.  Syntax: =TRIM(text)  The CLEAN function removes all non printable characters from the input.  Syntax: =CLEAN(text)

104. =Replace(A1, 1, 5, "Beta")would return "Betabet Soup" =Replace(A2, 5, 2, "1234")would return "Tech1234TheNet" =Replace("apples", 2, 5, "te")would return "ate"

105. DAVERAGE =DAVERAGE(database,field,criteria) DCOUNT =DCOUNT(database,field,criteria) DMAX =DMAX(database,field,criteria) DMIN =DMIN(database,field,criteria) DSUM =DSUM(database,field,criteria)

106. Microsoft ® Excel ® Database Functions Syntax: =DAVERAGE(database,field,criteria) Arguments: database Required  The range of cells that makes up the list or database. field Required  Indicates which column is used in the function. criteria Required  The range of cells that contains the conditions you specify.

107. Microsoft ® Excel ® Database Functions Description: Averages the values in a field (column) of records in a list or database that match conditions you specify. Remarks: You can use any range for the criteria argument, as long as it includes at least one column label and at least one cell below the column label for specifying the condition Although the criteria range can be located anywhere on the worksheet, do not place the criteria range below the list Make sure the criteria range does not overlap the list To perform an operation on an entire column in a database, enter a blank line below the column labels in the criteria range. Errors: None specified

108. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,"Yield",A1:B2) The average yield of apple trees over 10 feet in height.

109. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,"Yield",A1:B2) The average yield of apple trees over 10 feet in height.

110. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,"Yield",A1:B2) The average yield of apple trees over 10 feet in height.

111. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,"Yield",A1:B2) The average yield of apple trees over 10 feet in height.

112. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,"Yield",A1:B2) =12 The average yield of apple trees over 10 feet in height.

113. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10,3,A4:E10) The average age of all trees in the database.

114. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10, 3,A4:E10) The average age of all trees in the database.

115. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10, 3,A4:E10) The average age of all trees in the database.

116. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10, 3,A4:E10) The average age of all trees in the database.

117. Microsoft ® Excel ® Database Functions =DAVERAGE(A4:E10, 3,A4:E10) =13 The average age of all trees in the database.

118. Microsoft ® Excel ® Database Functions =DMAX(A4:E10,"Profit",A1:A3) The maximum profit of apple and pear trees.

119. Microsoft ® Excel ® Database Functions =DMAX(A4:E10,"Profit",A1:A3) The maximum profit of apple and pear trees.

120. Microsoft ® Excel ® Database Functions =DMAX(A4:E10,"Profit",A1:A3) The maximum profit of apple and pear trees.

121. Microsoft ® Excel ® Database Functions =DMAX(A4:E10,"Profit",A1:A3) The maximum profit of apple and pear trees.

122. Microsoft ® Excel ® Database Functions =DMAX(A4:E10,"Profit",A1:A3) =105 The maximum profit of apple and pear trees.

123. Microsoft ® Excel ® Database Functions =DMIN(A4:E10,"Profit",A1:B2) The minimum profit of apple trees over 10 in height.

124. Microsoft ® Excel ® Database Functions =DMIN(A4:E10,"Profit",A1:B2) The minimum profit of apple trees over 10 in height.

125. Microsoft ® Excel ® Database Functions =DMIN(A4:E10,"Profit",A1:B2) The minimum profit of apple trees over 10 in height.

126. Microsoft ® Excel ® Database Functions =DMIN(A4:E10,"Profit",A1:B2) The minimum profit of apple trees over 10 in height.

127. Microsoft ® Excel ® Database Functions =DMIN(A4:E10,"Profit",A1:B2) =75 The minimum profit of apple trees over 10 in height.

128. Microsoft ® Excel ® Database Functions =DCOUNT(A4:E10,"Age",A1:F2) This function looks at the records of apple trees between a height of 10 and 16 and counts how many of the Age fields in those records contain numbers.

129. Microsoft ® Excel ® Database Functions =DCOUNT(A4:E10,"Age",A1:F2) This function looks at the records of apple trees between a height of 10 and 16 and counts how many of the Age fields in those records contain numbers.

130. Microsoft ® Excel ® Database Functions =DCOUNT(A4:E10,"Age",A1:F2) This function looks at the records of apple trees between a height of 10 and 16 and counts how many of the Age fields in those records contain numbers.

131. Microsoft ® Excel ® Database Functions =DCOUNT(A4:E10,"Age",A1:F2) This function looks at the records of apple trees between a height of 10 and 16 and counts how many of the Age fields in those records contain numbers.

132. Microsoft ® Excel ® Database Functions =DCOUNT(A4:E10,"Age",A1:F2) =1 This function looks at the records of apple trees between a height of 10 and 16 and counts how many of the Age fields in those records contain numbers.

133. Microsoft ® Excel ® Database Functions =DSUM(A4:E10,"Profit",A1:A2) The total profit from apple trees.

134. Microsoft ® Excel ® Database Functions =DSUM(A4:E10,"Profit",A1:A2) The minimum profit of apple trees over 10 in height.

135. Microsoft ® Excel ® Database Functions =DSUM(A4:E10,"Profit",A1:A2) The minimum profit of apple trees over 10 in height.

136. Microsoft ® Excel ® Database Functions =DSUM(A4:E10,"Profit",A1:A2) The minimum profit of apple trees over 10 in height.

137. Microsoft ® Excel ® Database Functions =DSUM(A4:E10,"Profit",A1:A2) =225 The minimum profit of apple trees over 10 in height.

138.  Study the review questions at the textbook websites for the chapters covered in the final exam.  http://wps.prenhall.com/bp_kroenke_experie ncing_1/62/16106/4123157.cw/index.html http://wps.prenhall.com/bp_kroenke_experie ncing_1/62/16106/4123157.cw/index.html

140. Databases and Data Warehouses

141. There are two overall approaches to maintaining data: the traditional file approach—which has no mechanism for tagging, retrieving, and manipulating data—and the ____, which does have this mechanism. A) database approach B) data approach C) datafile approach D) indexed file approach

142. There are two overall approaches to maintaining data: the traditional file approach—which has no mechanism for tagging, retrieving, and manipulating data—and the ____, which does have this mechanism. A) database approach B) data approach C) datafile approach D) indexed file approach Ref. p 234

143.  Traditional file approach: no mechanism for tagging, retrieving, or manipulating data  Database approach: provides powerful mechanism for managing and manipulating data  Traditional approach is inconvenient:  Program-data dependency  High data redundancy  Low data integrity  Data redundancy: duplication of data  Data integrity: accuracy of data Management Information Systems, Sixth Edition143

144. Management Information Systems, Sixth Edition144

145. A database itself is a collection of several related files, but DBMSs do all the work—structuring files, storing data, and linking records. A) True B) False

146. A database itself is a collection of several related files, but DBMSs do all the work—structuring files, storing data, and linking records. A) True B) False Ref. P. 236

147. The very fact that manipulation of the data requires a programmer is probably the greatest disadvantage of the ____. A) information file approach B) file approach C) database approach D) indexed file approach

148. The very fact that manipulation of the data requires a programmer is probably the greatest disadvantage of the ____. A) information file approach B) file approach C) database approach D) indexed file approach Ref. p 234

149.  Database approach: data organized as entities  Entity: an object about which an organization chooses to collect data, such as:  People  Events  Products  Character: smallest piece of data  A single letter or a digit  Field: single piece of information about entity Management Information Systems, Sixth Edition149

150.  Record: collection of related fields  File: collection of related records  Database fields can hold images, sounds, video clips, etc.  Field name allows easy access to the data  Database management system (DBMS): program used to:  Build databases  Populate a database with data  Manipulate data in a database Management Information Systems, Sixth Edition150

151. Management Information Systems, Sixth Edition151

152. Management Information Systems, Sixth Edition152 The Database Approach (continued)  Database administrator (DBA): the person responsible for managing the database  Sets user limits for access to data in the database  DBMS is usually bundled with a programming language

153.  Relational Model: consists of tables  Based on relational algebra  Tuple: record (or row)  Attribute: field (or column)  Relation: table of records  To design a relational database, you must understand the entities to be stored in the database and how they relate  Tables are independent of each other, but can be related to each other Management Information Systems, Sixth Edition153

154. To link records from one table with records of another table, the tables must have at least one field in common, and that field must be a ____ field for one of the tables. A) composite key B) main key C) foreign key D) primary key

155. To link records from one table with records of another table, the tables must have at least one field in common, and that field must be a ____ field for one of the tables. A) composite key B) main key C) foreign key D) primary key Ref. p 240

156.  Key: a field whose values identify records  Used to retrieve records  Primary key: a field by which records are uniquely identified  Each record in the table must have a unique key value  Composite key: combination of fields that serve as a primary key Management Information Systems, Sixth Edition156

157. Management Information Systems, Sixth Edition157

158. Data is accessed in a database by sending messages called “protocols,” which request data from specific records and/or fields and direct the computer to display the results. A) True B) False

159. Data is accessed in a database by sending messages called “protocols,” which request data from specific records and/or fields and direct the computer to display the results. A) True B) False Ref. P. 237

160.  Query: a message to the database requesting data from specific records and/or fields  Database must be properly secured  Not everyone should have access to all data  Users will have different views of the database, based on the data they are allowed to see Management Information Systems, Sixth Edition160

161.  Foreign key: a field that is common to two tables  Used to link the tables  This field is a primary key in one table and a foreign key in the other  Join table: composite of tables  Two types of table relationships:  One-to-many relationship: one item in a table is linked to many items in the other table  Many-to-many relationship: many items in a table are linked to many items of the other table Management Information Systems, Sixth Edition161

162.  Object-oriented database model: uses object- oriented approach for the database structure  Encapsulation: combined storage of data and relevant procedures to process it  Allows object to be “planted” in different data sets  Inheritance: the ability to create a new object by replicating the characteristics of an existing (parent) object  Object-oriented databases (ODBs) store data objects, not records Management Information Systems, Sixth Edition162

163.  Relational operation: creates a temporary subset of a table or tables  Used to create a limited list or a joined table list  Three important relational operations:  Select: a selection of records based on conditions  Project: a selection of certain columns from a table  Join: join data from multiple tables to create a temporary table Management Information Systems, Sixth Edition163

164.  Structured Query Language (SQL): query language of choice for DBMSs  Advantages of SQL:  It is an international standard  It is provided with most relational DBMSs  It has easy-to-remember, intuitive commands Management Information Systems, Sixth Edition164

165. A ____ is the general logical structure in which records are stored within a database and the method used to establish relationships among the records. A) database relationship B) database model C) database list D) database catalog

166. A ____ is the general logical structure in which records are stored within a database and the method used to establish relationships among the records. A) database relationship B) database model C) database list D) database catalog Ref. p 238

167. A schema describes the structure of the database being designed: the names and types of fields in each record type and the general relationships among different sets of records or files. A) True B) False

168. A schema describes the structure of the database being designed: the names and types of fields in each record type and the general relationships among different sets of records or files. A) True B) False Ref. p 244

169.  Schema: a plan that describes the structure of the database, including:  Names and sizes of fields  Identification of primary keys  Relationships  Data dictionary: a repository of information about the data and its organization  Also called metadata: the data about the data Management Information Systems, Sixth Edition169

170. While a transactional database contains current data, which is disposed of after some time, the data in ____ is accumulated and might reflect many years of business activities. A) data warehouses B) data carts C) information bases D) information repositories

171. While a transactional database contains current data, which is disposed of after some time, the data in ____ is accumulated and might reflect many years of business activities. A) data warehouses B) data carts C) information bases D) information repositories Ref. p 248

172.  Most data collections are used for transactions  Accumulation of transaction data is useful  Data warehouse: a large repository database that supports management decision making  Typically relational  Data is collected from transactional databases  Data mart: a smaller collection of data focusing on a particular subject or department Management Information Systems, Sixth Edition172

173. Because of capacity needs, organizations often choose ____ to store and manage data warehouses. A) midrange servers B) high speed networks C) mainframe computers with multiple CPUs D) workstations

174. Because of capacity needs, organizations often choose ____ to store and manage data warehouses. A) midrange servers B) high speed networks C) mainframe computers with multiple CPUs D) workstations Ref. p 250

175.  Transactional databases are not suitable for business analysis  Contain only current, not historical data  Data warehouse requires large storage capacity:  Mainframe computers are often used  Scalability is an issue  Data warehouses grow continually Management Information Systems, Sixth Edition175

176. There are two phases involved in building a data warehouse from transactional data: extraction and transforming. A) True B) False

177. There are two phases involved in building a data warehouse from transactional data: extraction and transforming. A) True B) False Ref. p 251

178.  Three phases in transferring data from a transactional database to a data warehouse:  Extraction phase: create files from transactional database  Transformation phase: cleanse and modify the data format  Loading phase: transfer files to data warehouse  A properly built data warehouse becomes a single source for all data required for analysis  Data mining and online analytical processing (OLAP) use data in data warehouses Management Information Systems, Sixth Edition178